Template-Type: ReDIF-Article 1.0 Author-Name: Nguyen Van Hop Author-X-Name-First: Nguyen Van Author-X-Name-Last: Hop Title: Searching for the best profit-sharing allocation in multi-echelon supply chain Abstract: In this paper, we propose coordination procedures for a multi-echelon supply chain in which the appropriate profit-sharing rate is allocated for each supply chain member. The search process is first developed to maximise the total compromised profit of a two-member supply chain. From the achieved profit-sharing rate, the best ordering quantity is also determined. Then, a cascading procedure is also proposed for searching the best profit-sharing ratios for each member in the multi-echelon supply chain. Our proposed procedures are validated by comparing it with the fixed profit-sharing scheme. We have also investigated different scenarios to test the effect of demand variations on total cost at different profit-sharing rates. The obtained results are promising. [Submitted: 27 October 2020; Accepted: 22 January 2022] Journal: European J. of Industrial Engineering Pages: 148-167 Issue: 1 Volume: 17 Year: 2023 Keywords: supply chain coordination; profit sharing; multi-echelon supply chain. File-URL: http://www.inderscience.com/link.php?id=127749 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:1:p:148-167 Template-Type: ReDIF-Article 1.0 Author-Name: XueLong Hu Author-X-Name-First: XueLong Author-X-Name-Last: Hu Author-Name: Philippe Castagliola Author-X-Name-First: Philippe Author-X-Name-Last: Castagliola Author-Name: AnAn Tang Author-X-Name-First: AnAn Author-X-Name-Last: Tang Author-Name: XiaoJian Zhou Author-X-Name-First: XiaoJian Author-X-Name-Last: Zhou Title: Conditional design of the Shewhart X̄ chart with unknown process parameters based on median run length Abstract: Numerous researches have been done on the Shewhart <i>X̄</i> chart based on the average run length (<i>ARL</i>) metric. Since the shape of the run length (<i>RL</i>) distribution changes with the mean shift size, the median run length (<i>MRL</i>) is argued to be a better criterion for evaluating the performance of the Shewhart <i>X̄</i> chart. Moreover, when the process parameters are unknown, the phase 2 properties of the Shewhart <i>X̄</i> chart are conditioned on the parameter estimates arising from different practitioners in phase 1. This variability among the estimated process parameters is usually called as the between-practitioners variability. In order to investigate this variability in the conditional <i>MRL</i> values, both the average <i>MRL</i> (<i>AMRL</i>) and the standard deviation of <i>MRL</i> (<i>SDMRL</i>) will be used together in our article. The performance analyses of the <i>MRL</i>-based Shewhart <i>X̄</i> chart are provided. To prevent too many lower in-control <i>MRL</i> values than the desired one, an appropriate bootstrap approach is adopted to adjust the control limits, and to further balance the in- and out-of-control <i>MRL</i> values of the Shewhart <i>X̄</i> chart. [Submitted: 26 September 2018; Accepted: 15 January 2022] Journal: European J. of Industrial Engineering Pages: 90-114 Issue: 1 Volume: 17 Year: 2023 Keywords: Shewhart X̄ chart; median run length; estimated parameters; average median run length; Standard deviation of median run length. File-URL: http://www.inderscience.com/link.php?id=127753 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:1:p:90-114 Template-Type: ReDIF-Article 1.0 Author-Name: Adrian F. Rivera Author-X-Name-First: Adrian F. Author-X-Name-Last: Rivera Author-Name: Neale R. Smith Author-X-Name-First: Neale R. Author-X-Name-Last: Smith Author-Name: Esteban Ogazon Author-X-Name-First: Esteban Author-X-Name-Last: Ogazon Author-Name: Angel Ruiz Author-X-Name-First: Angel Author-X-Name-Last: Ruiz Title: A stochastic mixed-integer model to support foodbank resources prepositioning during the prelude to a natural disaster Abstract: A key strategic issue in pre-disaster planning for humanitarian logistics is the pre-establishment of adequate capacity and resources that enable efficient relief operations. Foodbanks must review their decisions and replan their activities upon the arrival of catastrophic events, such as earthquakes or floods. With the aim to support managers in the adaptation of their network and preparedness decisions during the prelude to the event, this paper presents a scenario-based stochastic mixed-integer optimisation formulation that aims to minimise the maximum amount of unfulfilled relief needs considering uncertainty both on the demand as well as on the availability of the infrastructure. The formulation was applied to the case of hurricane Odile that struck the Baja California Peninsula, Mexico, in 2014. Numerical experiments demonstrate that the solution reached by the proposed mathematical formulation improved the actual decisions that were made during the event. Further comparisons and analyses are presented. [Submitted: 19 October 2021; Accepted: 24 February 2022] Journal: European J. of Industrial Engineering Pages: 460-477 Issue: 3 Volume: 17 Year: 2023 Keywords: humanitarian logistics; HL; foodbanks; natural disasters; optimisation; scenarios; stochastic. File-URL: http://www.inderscience.com/link.php?id=130596 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:3:p:460-477 Template-Type: ReDIF-Article 1.0 Author-Name: Qiurui Liu Author-X-Name-First: Qiurui Author-X-Name-Last: Liu Author-Name: He Huang Author-X-Name-First: He Author-X-Name-Last: Huang Author-Name: Ziqiang Zeng Author-X-Name-First: Ziqiang Author-X-Name-Last: Zeng Author-Name: Lin Chen Author-X-Name-First: Lin Author-X-Name-Last: Chen Author-Name: Junren Ming Author-X-Name-First: Junren Author-X-Name-Last: Ming Title: An optimal supplier selection method for uncertain sustainable supply chains Abstract: This paper considers a sustainable supplier selection problem with uncertainty faced by a transportation authority. The buyer tends to choose the supplier who can maximise its sustainable objectives including economic, energy, and quality aspects. We study the changes of design and quality requirements, as well as the interactions of the variables in the public transport production industry that affect the supplier selection decision making. The multi-objective particle swarm optimisation (MOPSO) solution method is employed to solve the sustainable supplier selection problem under uncertainty. Based on the computational results, the proposed model can help the managers to reduce the supply chain risk of quality uncertainty and design uncertainty. Theoretically, we provide an initial model that incorporates sustainability into supplier selection for the transportation of products, taking into account design uncertainty and environmental dimension. Practically, we measure the impact of design indicator on procurement from the perspectives of operators and users. It can be beneficial to the application and the integration of sustainable supply chain management. [Submitted: 25 October 2021; Accepted: 24 February 2022] Journal: European J. of Industrial Engineering Pages: 431-459 Issue: 3 Volume: 17 Year: 2023 Keywords: sustainable supply chain; supplier selection; performance optimisation; decision-making model. File-URL: http://www.inderscience.com/link.php?id=130598 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:3:p:431-459 Template-Type: ReDIF-Article 1.0 Author-Name: Dony S. Kurian Author-X-Name-First: Dony S. Author-X-Name-Last: Kurian Author-Name: V. Madhusudanan Pillai Author-X-Name-First: V. Madhusudanan Author-X-Name-Last: Pillai Author-Name: J. Gautham Author-X-Name-First: J. Author-X-Name-Last: Gautham Author-Name: Akash Raut Author-X-Name-First: Akash Author-X-Name-Last: Raut Title: Data-driven imitation learning-based approach for order size determination in supply chains Abstract: Past studies have attempted to formulate the order decision-making behaviour of humans for inventory replenishment in dynamic stock management environments. This paper investigates whether a data-driven approach like machine learning can imitate the order size decisions of humans and consequently enhance supply chain performances. Accordingly, this paper proposes a supervised machine learning-based order size determination approach. The proposed approach is initially executed using the order decision data collected from a simulated stock management environment similar to the 'beer game'. Subsequent comparative analysis shows that the proposed approach successfully enhances all supply chain performance measures compared to other well-known ordering methods. Additionally, the proposed approach is validated on a retail case study to investigate its efficacy. This paper thus focuses on extending the past works reported in the literature by modelling human order decision-making as data-driven imitation learning and contributing to machine learning applications for order management. [Submitted: 19 August 2021; Accepted: 16 February 2022] Journal: European J. of Industrial Engineering Pages: 379-407 Issue: 3 Volume: 17 Year: 2023 Keywords: supply chain; order size determination; machine learning; behavioural experiments; LightGBM; imitation learning; beer game. File-URL: http://www.inderscience.com/link.php?id=130601 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:3:p:379-407 Template-Type: ReDIF-Article 1.0 Author-Name: Shih-Chou Kao Author-X-Name-First: Shih-Chou Author-X-Name-Last: Kao Title: Robust estimation of the process dispersion for standard deviation control charts Abstract: The detection ability of control charts varies with the robustness of estimators against contamination. The aim of this current study is to develop six types of estimators based on the scale A method with distributed weight functions and compare the performance of various dispersion control charts based on these functions under normal and contaminated normal environments. The values of their mean squared error are compared to those of existing estimators in diffuse and localised disturbances. The process-monitoring abilities of phase II control charts using phase I contaminated estimators are assessed using disturbances and process shifts. The estimator with the logistic distributed weight function performs the best against disturbances, with its average run lengths being closer to those in uncontaminated cases compared to other estimators. [Submitted: 15 December 2019; Accepted: 21 February 2022] Journal: European J. of Industrial Engineering Pages: 408-430 Issue: 3 Volume: 17 Year: 2023 Keywords: average run length; ARL; mean squared error; MSE; scale A estimator; trimming; weight function. File-URL: http://www.inderscience.com/link.php?id=130603 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:3:p:408-430 Template-Type: ReDIF-Article 1.0 Author-Name: Qianqian Zhu Author-X-Name-First: Qianqian Author-X-Name-Last: Zhu Author-Name: Xiuli Wang Author-X-Name-First: Xiuli Author-X-Name-Last: Wang Title: An auction mechanism for capacity allocation in identical parallel machines with time window constraints Abstract: We study the scarce production capacity allocation problem in a decentralised decision-making environment. We focus on the design of an auction mechanism for effective allocation of scarce capacity, without private information. In our problem setting, the firm's machine environment is identical parallel machines, and each customer order must be processed within a time window. Here, resource scarcity depends not only on capacity, but also on the customer orders' time window constraints. Hence, we propose an ascending auction with a discriminatory pricing scheme for customers, to identify the real processing requirements of the customer orders and resolve resource conflicts. In our auction, the winner determination problem is NP-complete, we develop a heuristic to solve this problem using the Lagrangian relaxation technique. The computational study shows that our auction mechanism achieves over 93% of the global optimal value. [Submitted 20 April 2021; Accepted 6 May 2022] Journal: European J. of Industrial Engineering Pages: 833-855 Issue: 6 Volume: 17 Year: 2023 Keywords: capacity allocation; auction mechanism; price discrimination; Lagrangian relaxation. File-URL: http://www.inderscience.com/link.php?id=134700 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:6:p:833-855 Template-Type: ReDIF-Article 1.0 Author-Name: Ardavan Babaei Author-X-Name-First: Ardavan Author-X-Name-Last: Babaei Author-Name: Majid Khedmati Author-X-Name-First: Majid Author-X-Name-Last: Khedmati Author-Name: Mohammad Reza Akbari Jokar Author-X-Name-First: Mohammad Reza Akbari Author-X-Name-Last: Jokar Title: Efficient hierarchical hybrid delivery in the last mile logistics Abstract: An efficient hierarchical hybrid delivery (EHHD) model is proposed by integrating a location-allocation optimisation model with a dynamic data envelopment analysis (DEA) model in this paper. The proposed model is characterised by having a periodic measurement assessing customer behaviour using the dynamic DEA, as well as developing a hierarchical connection among home delivery, the pickup point and the locker station options. The developed model considers uncertain conditions for transportation costs and customer behaviour. To solve this model, a meta-goal programming approach has been used. Based on the results of the numerical experiments, the developed model has a better performance than other competing models in terms of generating feasible and optimal solutions. Moreover, the application of the developed model is demonstrated in a case study. To the best of our knowledge, the model presented in this paper is the first attempt to simultaneously integrate customer behaviour with last-mile logistics. [Received: 23 April 2021; Accepted: 27 August 2022] Journal: European J. of Industrial Engineering Pages: 875-916 Issue: 6 Volume: 17 Year: 2023 Keywords: last-mile delivery; customer behaviour data; delivery options; hierarchical; efficient; supply chain. File-URL: http://www.inderscience.com/link.php?id=134701 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:6:p:875-916 Template-Type: ReDIF-Article 1.0 Author-Name: Lin Jiang Author-X-Name-First: Lin Author-X-Name-Last: Jiang Author-Name: Dongmei Liu Author-X-Name-First: Dongmei Author-X-Name-Last: Liu Author-Name: Shuaihui Tian Author-X-Name-First: Shuaihui Author-X-Name-Last: Tian Title: Decision-making and sub-coordination in a newsvendor model with a third party logistics service provider Abstract: This paper examines the logistics strategy in a newsvendor model and considers a supply chain (SC) comprising one manufacturer, one retailer, and one third party logistics service provider (TPLSP). The retailer is responsible for transporting the products from the manufacturer to the market, and it faces a decision problem whether the product logistics functions should be outsourced to the TPLSP. Logistics outsourcing will reduce logistics cost. However, logistics outsourcing also causes classic double marginalisation because of the price of the TPLSP. Only if the TPLSP's cost is small enough to cover double marginalisation, the logistics outsourcing can be accepted. This paper proposes a proper rule of logistics outsourcing and suggests reasonable outsourcing strategies of the retailer. Moreover, channel coordination after logistics outsourcing is discussed. Coordination schemes are often difficult to implement due to information sharing limits or administrative burden. Thus, coordination among some members of the SC, which we call sub-coordination, is easier to obtain than the coordination of all members. This paper studies two types of sub-coordination mechanisms and analyses how sub-coordination affects the newsvendor problem model with a TPLSP. [Submitted: 21 January 2022; Accepted: 31 August 2022] Journal: European J. of Industrial Engineering Pages: 917-938 Issue: 6 Volume: 17 Year: 2023 Keywords: newsvendor; logistics service provider; outsourcing; sub-coordination. File-URL: http://www.inderscience.com/link.php?id=134702 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:6:p:917-938 Template-Type: ReDIF-Article 1.0 Author-Name: Qiong Liu Author-X-Name-First: Qiong Author-X-Name-Last: Liu Author-Name: Qin Ye Author-X-Name-First: Qin Author-X-Name-Last: Ye Author-Name: Xu Mei Author-X-Name-First: Xu Author-X-Name-Last: Mei Author-Name: Qiang Zhang Author-X-Name-First: Qiang Author-X-Name-Last: Zhang Title: Inter-cell scheduling based on a transportation vehicle sharing strategy Abstract: In order to quickly respond to market demands and save investments on equipment, inter-cell manufacturing with flexible routes and candidate manufacturing cells is studied. An inter-cell scheduling model aiming at minimising total costs and makespan is proposed. Current transportation strategy (CTS) for inter-cell manufacturing might cause unloaded routes of vehicles, increase transportation costs and makespan. To reduce unloaded routes, a transportation vehicle sharing strategy (TVSS) in which exceptional parts could be transported by any vehicle in a manufacturing system and vehicles do not need to be returned to their original cells without load after one transportation is proposed. An improved shuffled frog leaping algorithm (ISFLA) is designed to solve the model. A case study and several random cases are used to verify the proposed TVSS. Results show that the proposed TVSS could reduce unloaded routes effectively and yield better solutions on both total costs and makespan than the CTS. [Received: 29 March 2021; Accepted: 16 September 2022] Journal: European J. of Industrial Engineering Pages: 939-973 Issue: 6 Volume: 17 Year: 2023 Keywords: cellular manufacturing; inter-cell scheduling; multi-objective optimisation; shuffled frog leaping algorithm; SFLA; current transportation strategy; CTS; transportation vehicle sharing strategy; TVSS; improved shuffled frog leaping algorithm; ISFLA. File-URL: http://www.inderscience.com/link.php?id=134703 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:6:p:939-973 Template-Type: ReDIF-Article 1.0 Author-Name: Weihua Liu Author-X-Name-First: Weihua Author-X-Name-Last: Liu Author-Name: Yanjie Liang Author-X-Name-First: Yanjie Author-X-Name-Last: Liang Author-Name: Xinran Shen Author-X-Name-First: Xinran Author-X-Name-Last: Shen Title: Decentralised or collaborative? Cooperation strategy choice of the supply chain under logistics service integrator empowerment and market size fluctuation Abstract: Nowadays, the logistics service integrator (LSI) improves service quality by empowering the functional logistics service provider (FLSP). Meanwhile, there are two cooperation strategies: decentralised strategy and collaborative strategy. On this basis, we explore: 1) the cooperation strategy choice of the supply chain members; 2) the impact of the market size fluctuation on their strategy choice. The main findings are as follows. First, when the revenue-sharing coefficient is in the middle range, both the LSI and the FLSP choose the collaborative strategy. Second, when the market size is higher than a certain threshold, no matter what strategy is implemented in the first period, supply chain members are more inclined to choose the decentralised strategy rather than the collaborative strategy in the second period. Third, we find that information asymmetry causes the supply chain members to deviate from optimal decisions, which restrains the collaborative strategy from becoming the equilibrium strategy. [Submitted: 14 May 2021; Accepted: 12 February 2022] Journal: European J. of Industrial Engineering Pages: 343-378 Issue: 3 Volume: 17 Year: 2023 Keywords: logistics service supply chain; LSSC; empowerment; market size fluctuation; cooperation strategy. File-URL: http://www.inderscience.com/link.php?id=130607 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:3:p:343-378 Template-Type: ReDIF-Article 1.0 Author-Name: Zhangwei Feng Author-X-Name-First: Zhangwei Author-X-Name-Last: Feng Author-Name: Na Luo Author-X-Name-First: Na Author-X-Name-Last: Luo Author-Name: Bisheng Du Author-X-Name-First: Bisheng Author-X-Name-Last: Du Author-Name: Haorui Wang Author-X-Name-First: Haorui Author-X-Name-Last: Wang Title: Third-party remanufacturing modes with integrated tax-subsidy policy Abstract: Tax-subsidy policy is a common government intervention mechanism to stimulate firms taking part in sustainable remanufacturing operations. Focusing on the third-party remanufacturing strategy (outsourcing or authorisation), this paper develops game models to study the trade-offs between manufactures and third-party remanufactures. Unlike the existing literature, we particularly include the feature of green consumers and the government intervention into the analytical model. The findings of this paper include: 1) manufactures choose authorisation when consumers show no green preferences; 2) third-party remanufactures need actions to improve green consumer preference for achieving high profit; 3) when unit carbon tax is high, manufacturers select authorisation; otherwise, outsourcing; 4) outsourcing strategy is beneficial to environmental sustainability and social welfare. [Submitted: 8 September 2021; Accepted: 17 July 2022] Journal: European J. of Industrial Engineering Pages: 740-765 Issue: 5 Volume: 17 Year: 2023 Keywords: outsourcing; authorisation; product quality; green consumer preference; integrated tax-subsidy; game theory. File-URL: http://www.inderscience.com/link.php?id=133168 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:5:p:740-765 Template-Type: ReDIF-Article 1.0 Author-Name: Xin Zhang Author-X-Name-First: Xin Author-X-Name-Last: Zhang Author-Name: David Mendonça Author-X-Name-First: David Author-X-Name-Last: Mendonça Title: Temporal aspects of trade-offs in organisational performance: an illustration from post-disaster debris removal Abstract: Trade-offs - between risk and reward, efficiency and effectiveness - are endemic to an organisation's evolution and success. Until recently, however, organisational performance studies have suffered from a lack of detailed, longitudinal data, and therefore of methods that could exploit these data. While many organisations now deploy instrumentation to collect data on operations, those data are seldom directly suited to researchers' aims and are therefore characterised as 'secondary'. This paper addresses this two-fold gap by casting secondary data within a theoretically grounded measurement framework and employing an innovative approach - based on data envelopment analysis - to assessing the additional value provided by the data's temporal aspects. The domain of application, post-disaster debris removal, is time-constrained, potentially expensive, and crucial to post-disaster recovery. The results of this study strongly suggest the relevance of temporal aspects of the data to modelling of performance trade-offs, but also the need for further development of novel methodological approaches to examining performance trade-offs. [Received: 24 November 2020; Accepted: 7 August 2022] Journal: European J. of Industrial Engineering Pages: 856-874 Issue: 6 Volume: 17 Year: 2023 Keywords: disaster response; organisational performance; trade-offs; secondary data; data envelopment analysis; time series; correlation analysis. File-URL: http://www.inderscience.com/link.php?id=134706 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:6:p:856-874 Template-Type: ReDIF-Article 1.0 Author-Name: Xiao Li Author-X-Name-First: Xiao Author-X-Name-Last: Li Author-Name: Hongfei Liang Author-X-Name-First: Hongfei Author-X-Name-Last: Liang Author-Name: Yuchen Chen Author-X-Name-First: Yuchen Author-X-Name-Last: Chen Author-Name: Yuanpeng Ruan Author-X-Name-First: Yuanpeng Author-X-Name-Last: Ruan Author-Name: Lei Wang Author-X-Name-First: Lei Author-X-Name-Last: Wang Title: A collaborative model for predictive maintenance of after-sales equipment based on digital twin Abstract: In response to the demands of users for prompting fault diagnosis and maintenance, equipment manufacturers require more advanced maintenance technologies for real-time monitoring, prediction, and remote guidance. Based on digital twin, this paper puts forward a seven-dimensional model of collaborative maintenance and a collaborative model for after sales maintenance service, which enables manufacturers to provide more effective and timely service and support to their customers. Taking a bottled water capping process as an example, it constructs a digital twin-driven model for predicting the remaining effective life of devices, a digital twin service platform with a maintenance knowledge database. Based on the forward variable combining the current state and state duration from hidden semi-Markov chain, and the improved formula for calculating the remaining effective life of equipment state, the feasibility of the proposed seven-dimensional collaborative maintenance model and the collaborative model for after sales maintenance service are verified. [Submitted: 20 July 2021; Accepted: 8 August 2022] Journal: European J. of Industrial Engineering Pages: 795-831 Issue: 5 Volume: 17 Year: 2023 Keywords: digital twin; predictive maintenance; collaborative maintenance; hidden semi-Markov chain model; after-sales equipment. File-URL: http://www.inderscience.com/link.php?id=133174 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:5:p:795-831 Template-Type: ReDIF-Article 1.0 Author-Name: Bappa Mondal Author-X-Name-First: Bappa Author-X-Name-Last: Mondal Author-Name: Arindam Garai Author-X-Name-First: Arindam Author-X-Name-Last: Garai Author-Name: Tapan Kumar Roy Author-X-Name-First: Tapan Kumar Author-X-Name-Last: Roy Title: Operational strategies of fuzzy inventory models for costly metallic items with conditional trade-credit policy linked to purchasing cost Abstract: The present study investigates an inventory system of the costly metallic items with steadily increasing demand rate and partial back-ordering under volatile market conditions. In contrast to conventional norms, the suppliers of those costly products often opt for the conditional trade-credit policy to overcome the retailers' reluctance regarding their procurement in larger quantities. Accordingly, there appear six different variants of the proposed inventory model according to the accumulated fund with the retailer at the settlement time of account. This study employs the well-established total λ-integral approach to defuzzify various triangular fuzzy cost coefficients and interest rates of the proposed model. Thereafter, this study analytically establishes the global optimality of the proposed model by collectively considering six results. The managerial insights plead to the legislators to provide several financial stimulus to uplift the business condition, whenever that turns gloomy. When the supplier boosts the value of order quantity to offer the full delay, the impact of promoting the retailers' demand turns negative. [Submitted: 26 April 2020; Accepted: 3 July 2022] Journal: European J. of Industrial Engineering Pages: 696-739 Issue: 5 Volume: 17 Year: 2023 Keywords: inventory model; conditional trade-credit; accumulated fund; partial back-ordering; costly metallic item; volatile market. File-URL: http://www.inderscience.com/link.php?id=133183 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:5:p:696-739 Template-Type: ReDIF-Article 1.0 Author-Name: Ayse Burcu Sanan Author-X-Name-First: Ayse Burcu Author-X-Name-Last: Sanan Author-Name: Meral Azizoğlu Author-X-Name-First: Meral Author-X-Name-Last: Azizoğlu Title: An integrated two dimensional cutting stock and lot sizing problem with two criteria Abstract: In this study, we consider an integrated two dimensional cutting stock and lot sizing problem arising in an aircraft manufacturing plant. The items are to be cut from steel panels of identical size to satisfy all periodic demands over a specified planning horizon. Two objectives, minimising the number of panels cut and the total inventory carrying cost of the items, are defined and all non-dominated objective vectors concerning the defined objectives are generated. To generate each non-dominated objective vector, we propose a mixed integer linear programming model whose efficiency is improved by optimality properties and bounding mechanisms. The results of our experiments have revealed that the instances with few items can be solved for up to 14 periods and the instances with more items can be solved for up to seven periods, in two hours. [Submitted: 29 March 2022; Accepted: 7 August 2022] Journal: European J. of Industrial Engineering Pages: 766-794 Issue: 5 Volume: 17 Year: 2023 Keywords: two dimensional cutting stock problems; 2DCSPs; lot sizing problems; integrated problems; multi-objective programming. File-URL: http://www.inderscience.com/link.php?id=133205 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:5:p:766-794 Template-Type: ReDIF-Article 1.0 Author-Name: Bruna Tamara de Lima Author-X-Name-First: Bruna Tamara de Author-X-Name-Last: Lima Author-Name: Gilberto Miller Devós Ganga Author-X-Name-First: Gilberto Miller Devós Author-X-Name-Last: Ganga Author-Name: Moacir Godinho Filho Author-X-Name-First: Moacir Godinho Author-X-Name-Last: Filho Author-Name: Luis Antonio de Santa-Eulalia Author-X-Name-First: Luis Antonio de Author-X-Name-Last: Santa-Eulalia Title: Blockchain capabilities for supply chain management Abstract: Blockchain is a novel technology that has attracted supply chain management (SCM) interest. As the literature suggests the positive effect of such technology on SCM, this study aims to provide a systematic understanding of blockchain capabilities for SCM (BCSCM). Focusing on resource-based view (RBV) and composition-based view (CBV) theories, a systematic literature review is performed to map BCSCM, their main supporting resources, and the competitive advantages generated. A framework is proposed to highlight and explain the combined use of RBV and CBV. BCSCM are presented and categorised according to the different competitive advantages they can lead to. The relationship between resources, BCSCM, and competitive advantages is discussed. To the best of the authors' knowledge, the literature lacks a systematic review exploring BCSCM from the combined RBV-CBV perspective. Further, the identification, proposition, and linkage between the capabilities, competitive advantages, and resources, as well as a final BCSCM classification, have not previously been addressed in the literature. [Submitted: 17 September 2021; Accepted: 25 June 2022] Journal: European J. of Industrial Engineering Pages: 657-695 Issue: 5 Volume: 17 Year: 2023 Keywords: blockchain capabilities; supply chain management; SCM; resource-based view; composition-based view; information and communication technology; distributed ledger technology; DLT; blockchain benefits; blockchain advantages; digital supply chains; competitive advantages; Industry 4.0; digitalisation. File-URL: http://www.inderscience.com/link.php?id=133214 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:5:p:657-695 Template-Type: ReDIF-Article 1.0 Author-Name: Dalila Tayachi Author-X-Name-First: Dalila Author-X-Name-Last: Tayachi Author-Name: Cheima Jendoubi Author-X-Name-First: Cheima Author-X-Name-Last: Jendoubi Title: Optimising green vehicle routing problem - a real case study Abstract: The optimisation of distribution activities in the logistics scheme of various companies, long time based on economic objectives, is widening today to integrate environmental concerns. This paper addresses the fuel consumption minimisation problem for one variant of the green VRP which is the VRP with fuel consumption rate (FCVRP) and considers load and distance as two main factors affecting fuel consumption. The problem is classified as NP-hard, hence, we propose to solve it by an iterated local search meta-heuristic (ILSFC-SP) starting with a heuristic approach that is based on mathematical programming and generates solutions by CPLEX. In order to test its performance, ILSFC-SP was first applied on benchmark instances to minimise fuel consumption as well as travelled distance and compared with the literature where it proved its efficacy, then, it was applied to a real-world application in Tunisia where it suggested operational solutions reducing considerably the fuel costs. [Submitted: 28 June 2019; Accepted: 17 April 2022] Journal: European J. of Industrial Engineering Pages: 570-596 Issue: 4 Volume: 17 Year: 2023 Keywords: fuel consumption; green vehicle routing problem; iterated local search; logistics; set-partitioning problem. File-URL: http://www.inderscience.com/link.php?id=131732 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:4:p:570-596 Template-Type: ReDIF-Article 1.0 Author-Name: Di Wu Author-X-Name-First: Di Author-X-Name-Last: Wu Author-Name: Peng Li Author-X-Name-First: Peng Author-X-Name-Last: Li Author-Name: Juhong Chen Author-X-Name-First: Juhong Author-X-Name-Last: Chen Author-Name: Hao Wang Author-X-Name-First: Hao Author-X-Name-Last: Wang Title: Coordination strategies of dual channel closed-loop supply chain considering demand disruptions Abstract: From the perspective of emergency management, it is of great practical significance to study the effect of demand disruptions on the decisions of dual channel closed-loop supply chain. Firstly, based on Stackelberg game theory, this paper constructs and solves the game model of dual channel closed-loop supply chain in centralised and decentralised decision modes, and analyses the effect of positive and negative demand disruptions on the optimal decision and profit of enterprises. Secondly, the construction of revenue-cost sharing contract realises the coordination between online and offline channels. Finally, a numerical example is used to further explore the effects of the factors on the equilibrium solution. The results show that: 1) when the degree of demand disruptions is small, the decision has certain robustness; 2) when demand has a negative disruption, the manufacturer will consider helping the retailer to reduce the loss on the premise of giving priority to reducing its own profit loss. Such behaviour is a typical 'sharing joys but not sorrows'. [Submitted: 23 December 2021; Accepted: 30 April 2022] Journal: European J. of Industrial Engineering Pages: 597-626 Issue: 4 Volume: 17 Year: 2023 Keywords: demand disruptions; dual channel closed-loop supply chain; recovery rate; pricing strategies; coordination strategies. File-URL: http://www.inderscience.com/link.php?id=131733 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:4:p:597-626 Template-Type: ReDIF-Article 1.0 Author-Name: Farid Abdi Author-X-Name-First: Farid Author-X-Name-Last: Abdi Author-Name: Hiwa Farughi Author-X-Name-First: Hiwa Author-X-Name-Last: Farughi Author-Name: Heibatolah Sadeghi Author-X-Name-First: Heibatolah Author-X-Name-Last: Sadeghi Author-Name: Jamal Arkat Author-X-Name-First: Jamal Author-X-Name-Last: Arkat Title: Location-inventory-reliability optimisation problem in a multi-objective multi-period three-level supply chain network with stochastic demand Abstract: One of the efficient methods of improving the reliability of factories is allocating appropriate redundant components that play an important role in responding to customers' demands, timely delivery and cost reduction. In this study, the issue of simultaneous optimisation of facility location-inventory-redundancy allocation has been investigated. In this regard, a multiple-period three-level problem has been taken into account. It has been assumed that demand for each retailer is stochastic and follows the normal distribution. In order to deal with the fluctuations of demand, the risk pooling effect has been applied. For this purpose, an integer nonlinear programming model has been proposed to optimise the cost of the supply chain as well as its reliability. Since facility location-inventory and redundancy allocation are categorised as NP-hard problems, non-dominated sorting genetic algorithm (NSGA-II) and archived multi-objective simulated annealing (AMOSA) algorithms have been developed for solving the aforementioned problem. Finally, their results have been evaluated by using comparison metrics of multi-objective algorithms. [Submitted: 9 September 2021; Accepted: 9 March 2022] Journal: European J. of Industrial Engineering Pages: 479-528 Issue: 4 Volume: 17 Year: 2023 Keywords: supply chain management; location-inventory model; redundancy allocation; stochastic demand; risk pooling; non-dominated sorting genetic algorithm II; NSGA-II; archive multi-objective simulated annealing; Taguchi methods. File-URL: http://www.inderscience.com/link.php?id=131743 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:4:p:479-528 Template-Type: ReDIF-Article 1.0 Author-Name: Gustavo Franco Barbosa Author-X-Name-First: Gustavo Franco Author-X-Name-Last: Barbosa Author-Name: Pedro Henrique da Silva Guedes Author-X-Name-First: Pedro Henrique da Silva Author-X-Name-Last: Guedes Author-Name: Sidney Bruce Shiki Author-X-Name-First: Sidney Bruce Author-X-Name-Last: Shiki Author-Name: Iris Bento da Silva Author-X-Name-First: Iris Bento da Author-X-Name-Last: Silva Author-Name: Guylherme Emmanuel Tagliaferro de Queiroz Author-X-Name-First: Guylherme Emmanuel Tagliaferro de Author-X-Name-Last: Queiroz Title: A novel QFD-based analytical guideline approach for painting applicator nozzle selection Abstract: This paper proposes a novel quality function deployment (QFD) based analytical guideline, concepted to assist the choice of applicator nozzles for painting systems of any business. The lack of specific guidance methods for this purpose is often the cause of difficulties experienced by industries during the selection of painting applicators. So, an analytical guideline assisted by a customised QFD approach is proposed to analyse all key painting parameters to be assessed and cross-checked with the strategy of a given business. It allows to determine the main technical features that should be considered during the decision process, by a calculation of scores of each painting system. The purpose is to orient the industrial needs related to manufacturing strategies to be used by engineers, managers and project leaders who are in charge of specifying painting systems and making strategic decisions. To attest that, two case studies have been conducted to demonstrate the application of the proposed approach. Thus, this contribution looks for better results in terms of productivity and quality on painting routines, oriented to the company's strategy of costs reduction and adding competitive value to the business. [Submitted: 14 June 2021; Accepted: 3 July 2022] Journal: European J. of Industrial Engineering Pages: 627-656 Issue: 4 Volume: 17 Year: 2023 Keywords: quality function deployment; QFD; analytical guideline; decision process; painting; manufacturing. File-URL: http://www.inderscience.com/link.php?id=131745 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:4:p:627-656 Template-Type: ReDIF-Article 1.0 Author-Name: Imen Mejri Author-X-Name-First: Imen Author-X-Name-Last: Mejri Author-Name: Safa Bhar Layeb Author-X-Name-First: Safa Bhar Author-X-Name-Last: Layeb Author-Name: Farah Zeghal Author-X-Name-First: Farah Author-X-Name-Last: Zeghal Title: A survey on network design problems: main variants and resolution approaches Abstract: Over the last decades, network design problems (NDPs) have been one of the most investigated combinatorial optimisation problems that are still catching the interest of both practitioners and researchers. In fact, <i>NDPs</i> pose significant algorithmic challenges, as they are notoriously <i>NP</i>-hard, and arise in several applications, mainly in logistics, telecommunication, and production systems. Based on the literature published mainly between 1962 and 2021, this paper provides a comprehensive taxonomy of <i>NDPs</i> and also identifies the most investigated variants as well as their main fields of application. This taxonomy highlights the diversity as well as the assets of this core class of operations research problems. Moreover, the main mathematical formulations and solution methods are reported. Finally, directions for future research on <i>NDPs</i> are derived. [Submitted: 14 March 2021; Accepted: 23 January 2022] Journal: European J. of Industrial Engineering Pages: 253-309 Issue: 2 Volume: 17 Year: 2023 Keywords: network design problems; NDPs; literature review; survey; combinatorial optimisation. File-URL: http://www.inderscience.com/link.php?id=129443 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:2:p:253-309 Template-Type: ReDIF-Article 1.0 Author-Name: Ying Xu Author-X-Name-First: Ying Author-X-Name-Last: Xu Author-Name: Xiao Zhao Author-X-Name-First: Xiao Author-X-Name-Last: Zhao Author-Name: Pengcheng Dong Author-X-Name-First: Pengcheng Author-X-Name-Last: Dong Author-Name: Guodong Yu Author-X-Name-First: Guodong Author-X-Name-Last: Yu Title: Risk-averse joint facility location-inventory optimisation for green closed-loop supply chain network design under demand uncertainty Abstract: This paper considers a joint facility location-inventory optimisation for green closed-loop supply chain network design under demand uncertainty. Under the uncoordinated inventory policy, we propose a chance-constrained risk-averse bi-objective 0-1 mixed-integer nonlinear stochastic programming to minimise the total expected cost and CO<SUB align="right"><SMALL>2</SMALL></SUB> emissions. To solve the model, we first present an equivalent reformulation with a single objective based on distributionally robust optimisation. Then, we provide a linear reformulation with some valid inequalities. We also provide a greedy heuristic decomposition searching rule to solve the large-scale problem. We finally present a numerical analysis to show the performance of our methods. Results illustrate that the risk-averse joint model can effectively improve service capability and reliability than independent and risk-neutral location and inventory problems. We also recommend that the incompletely uncoordinated strategy for the joint optimisation can be more cost-effective and generate fewer workloads. Besides, the proposed algorithm achieves a more desirable performance than CPLEX for large-scale problems. [Submitted: 10 December 2020; Accepted: 15 January 2022] Journal: European J. of Industrial Engineering Pages: 192-219 Issue: 2 Volume: 17 Year: 2023 Keywords: green closed-loop supply chain; facility location; inventory; risk-averse; chance constraint; distributionally robust optimisation. File-URL: http://www.inderscience.com/link.php?id=129444 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:2:p:192-219 Template-Type: ReDIF-Article 1.0 Author-Name: Mehmet Pınarbaşı Author-X-Name-First: Mehmet Author-X-Name-Last: Pınarbaşı Author-Name: Mustafa Yüzükırmızı Author-X-Name-First: Mustafa Author-X-Name-Last: Yüzükırmızı Title: A new framework for balancing and performance evaluation in stochastic assembly line using queueing networks Abstract: Real world assembly lines have a characterisation of variability in arrival, service and departure processes. Modelling these variabilities and their interactions, and the optimisation of a line have not been achieved yet. The purpose of this research is to provide an analytical solution framework for finding the best combinations of task assignment under variability. A queueing-based decomposition model that considers all variations sources has been proposed for the performance evaluation of a stochastic assembly line. A closed, nonlinear constraint programming model has been developed. Mathematical relations from the variability sources are established to measure the overall system performance. Numerical experiments which are conducted on several numerical examples demonstrate that the approach is a viable and an effective solution method. The results also indicate that changes in the coefficient of variance of either the service or arrival process, alter both the task assignment combinations, station workloads and line performance. [Submitted: 10 July 2021; Accepted: 19 January 2022] Journal: European J. of Industrial Engineering Pages: 220-252 Issue: 2 Volume: 17 Year: 2023 Keywords: stochastic assembly line balancing; variability; queueing network; constraint programming; decomposition; simulation. File-URL: http://www.inderscience.com/link.php?id=129445 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:2:p:220-252 Template-Type: ReDIF-Article 1.0 Author-Name: Jun Chang Author-X-Name-First: Jun Author-X-Name-Last: Chang Author-Name: Wenjie Dong Author-X-Name-First: Wenjie Author-X-Name-Last: Dong Author-Name: Zhigeng Fang Author-X-Name-First: Zhigeng Author-X-Name-Last: Fang Title: Implementing a bivariate preventive maintenance strategy for stochastically deteriorating systems with two types of shocks Abstract: This paper mainly investigates a preventive replacement policy for a system subject to both a deteriorating process and a shock process. Firstly, the stochastic deterioration is modelled with a general degradation path model, and the arrival numbers of external shocks are described with a non-homogeneous Poisson process (NHPP). The two processes are mutually dependent and the shock process itself has two distinct effectiveness including a minor one and a major one. Afterwards, system reliability function is constructed analytically. Finally, a bivariate preventive maintenance policy is put forward. The average maintenance cost rate is formulated and optimised for two special cases, respectively. To demonstrate the effectiveness of the proposed model, a sliding spool in a realistic hydraulic control system is studied. [Submitted: 14 October 2021; Accepted: 2 January 2022] Journal: European J. of Industrial Engineering Pages: 169-191 Issue: 2 Volume: 17 Year: 2023 Keywords: degradation modelling; random shocks; mutual dependence; two types of shocks; preventive maintenance. File-URL: http://www.inderscience.com/link.php?id=129450 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:2:p:169-191 Template-Type: ReDIF-Article 1.0 Author-Name: Weihua Liu Author-X-Name-First: Weihua Author-X-Name-Last: Liu Author-Name: Shuang Wei Author-X-Name-First: Shuang Author-X-Name-Last: Wei Author-Name: Xinran Shen Author-X-Name-First: Xinran Author-X-Name-Last: Shen Author-Name: Yanjie Liang Author-X-Name-First: Yanjie Author-X-Name-Last: Liang Title: Coordination mechanism of logistic service supply chain: a perspective of presale sinking and risk aversion Abstract: Many retailers are implementing presale strategies with logistics integrator for presale sinking, and pre-distributing products to sinking sites in advance, to conveniently and efficiently deliver to customers. This paper explores the influence of presale strategies and risk-averse behaviour on decisions and profits of the logistics integrator in the context of demand updating. The paper finds that when retailer adopts presale strategies with a larger discount, all potential customers will pre-order in the first period; otherwise, all potential customers will buy in the second period. These presale strategies can increase the pre-distribution volume and utility of the logistics integrator. While the risk-averse behaviour leads to a decrease in the pre-delivery volume, the utility of logistics integrator increases. Under these presale strategies, high discounts can eliminate the impact of uncertain demand risk, while presale strategies with low discounts cannot. [Submitted: 24 October 2021; Accepted: 3 February 2022] Journal: European J. of Industrial Engineering Pages: 310-341 Issue: 2 Volume: 17 Year: 2023 Keywords: presale sinking; risk aversion; logistics pre-distribution; conditional value-at-risk; CVaR. File-URL: http://www.inderscience.com/link.php?id=129459 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:2:p:310-341 Template-Type: ReDIF-Article 1.0 Author-Name: Lydia Bazizi Author-X-Name-First: Lydia Author-X-Name-Last: Bazizi Author-Name: Fazia Rahmoune Author-X-Name-First: Fazia Author-X-Name-Last: Rahmoune Author-Name: Ouiza Lekadir Author-X-Name-First: Ouiza Author-X-Name-Last: Lekadir Author-Name: Karim Labadi Author-X-Name-First: Karim Author-X-Name-Last: Labadi Title: Modelling, performance evaluation and optimisation of (s, Q) retrial inventory system with partial backlogging demands: a GSPN approach Abstract: In this article, we model and analyse by using generalised stochastic Petri nets (GSPNs), an inventory system according to the (<i>s</i>, <i>Q</i>) replenishment policy, Poissonian batch arrivals in deterministic size <i>n</i>, immediate batch service and retrials. In out-of-stock situation, the arriving demands at the system join a limited orbit, if it is not full, and retry again after a random time exponentially distributed, following the classic retrial policy. However, in the case of a full orbit, these demands are definitively rejected from the system. We describe the dynamic of this inventory system using a two-dimensional continuous time Markov chain (CTMC), which expresses the inventory level and the number of demands in the orbit. Then, we recover the stationary distribution, using a recursive algorithm, from which we derive various performance measures. Finally, we investigate some numerical analysis of the reward-cost function induced by this model. [Submitted: 2 June 2021; Accepted: 28 March 2022] Journal: European J. of Industrial Engineering Pages: 529-569 Issue: 4 Volume: 17 Year: 2023 Keywords: inventory control system; (s, Q) policy; generalised stochastic Petri nets; GSPNs; continuous time Markov chain; CTMC; recursive algorithm; reward-cost function. File-URL: http://www.inderscience.com/link.php?id=131778 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:4:p:529-569 Template-Type: ReDIF-Article 1.0 Author-Name: Maryam Radman Author-X-Name-First: Maryam Author-X-Name-Last: Radman Author-Name: Kourosh Eshghi Author-X-Name-First: Kourosh Author-X-Name-Last: Eshghi Title: Solving airline crew pairing problems through constraint partitioning Abstract: In this paper, a decomposition technique based on constraint partitioning is developed to solve the crew pairing problem (CPP) which has an overriding importance in the airline industry as it determines the crew cost. The method is based on the observation that in large-scale problems, the constraints can be partitioned to some sub-problems which involve special subsets of variables. The resultant structure is called the 'partitioned structure'. Therefore, in the proposed method, first, a feasible solution is generated for a reduced CPP with a 'partitioned structure' through the optimal solutions of its sub-problems. Then, at each step, the feasible solution is improved through adding/removing some pairings to/from it. The proposed algorithm is applied to a case study from the literature as well as some randomly generated test problems. One advantage of the proposed method is finding multiple feasible solutions with lower time than the method used to solve the case. [Submitted: 8 May 2020; Accepted: 29 December 2021] Journal: European J. of Industrial Engineering Pages: 29-59 Issue: 1 Volume: 17 Year: 2023 Keywords: crew pairing problems; CPPs; constraint partitioning; decomposition technique; sub-problem; airline industry. File-URL: http://www.inderscience.com/link.php?id=127738 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:1:p:29-59 Template-Type: ReDIF-Article 1.0 Author-Name: Jalal Taji Author-X-Name-First: Jalal Author-X-Name-Last: Taji Author-Name: Hiwa Farughi Author-X-Name-First: Hiwa Author-X-Name-Last: Farughi Author-Name: Hasan Rasay Author-X-Name-First: Hasan Author-X-Name-Last: Rasay Title: An integrated Markov chain model for the economic-statistical design of adaptive multivariate control charts and maintenance planning Abstract: In this paper, the mean of a process with several quality characteristics is monitored using a multivariate control chart which is a variable parameter (<i>Vp</i>) chi-square control chart with two types of sampling schemes. For this purpose, using the property of Markov chains, an integrated model is developed that coordinates the decisions related to the economic-statistical design of the control chart and maintenance planning. In the case of failure, the system will shut down automatically and a corrective maintenance activity will be performed immediately. Preventive maintenance activity is implemented when an out-of-control state is correctly identified. To evaluate the economic efficiency of the proposed model, a comparison between its optimum cost and the optimum cost of a multivariate exponentially weighted moving average (MEWMA) control chart and also a model that applies a chi-square control chart with fixed parameter is provided. Moreover, constraints related to <i>ARL</i><SUB align="right"><SMALL>0</SMALL></SUB> and <i>ARL</i><SUB align="right"><SMALL>1</SMALL></SUB> have been taken into account to ensure the statistical performance of the model. The results of the numerical analyses show a significant improvement in the cost per time unit. [Submitted: 23 November 2020; Accepted: 28 November 2021] Journal: European J. of Industrial Engineering Pages: 1-28 Issue: 1 Volume: 17 Year: 2023 Keywords: integrated model; quality control; chi-square control chart; maintenance planning. File-URL: http://www.inderscience.com/link.php?id=127739 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:1:p:1-28 Template-Type: ReDIF-Article 1.0 Author-Name: Natalia Roberta Lopes Author-X-Name-First: Natalia Roberta Author-X-Name-Last: Lopes Author-Name: Moacir Godinho Filho Author-X-Name-First: Moacir Godinho Author-X-Name-Last: Filho Author-Name: Gilberto Miller Devós Ganga Author-X-Name-First: Gilberto Miller Devós Author-X-Name-Last: Ganga Author-Name: Guilherme Luz Tortorella Author-X-Name-First: Guilherme Luz Author-X-Name-Last: Tortorella Author-Name: Mario Henrique Bueno Moreira Callefi Author-X-Name-First: Mario Henrique Bueno Moreira Author-X-Name-Last: Callefi Author-Name: Bruna Tamara de Lima Author-X-Name-First: Bruna Tamara de Author-X-Name-Last: Lima Title: Critical factors for sustaining lean manufacturing in the long-term: a multi-method study Abstract: In recent years, lean manufacturing (LM) has been used to improve the operational performance of organisations by improving the productivity, quality and profitability of their operations. However, some authors claim that these organisations are struggling to implement and maintain lean initiatives in a sustainable way over time. This paper proposes a list of critical factors for sustaining LM in the long-term. We used a multi-method research approach. First, we generated a list of critical factors for sustaining LM in the long-term using the systematic literature review approach. Subsequently, interviews with experts were used to refine these factors. Following this, two case studies were performed, and the results passed through another round of interviews with experts to ensure the robustness of the results. The main result of the research is a list of 19 LM sustainability factors. To the best of the authors' knowledge, this is the first research to propose a scientifically validated list of critical factors for sustaining LM. The contribution of this work lies in consolidating the lean sustainability factors widely found in the literature. In practical terms, the proposed list can guide managerial efforts towards sustaining lean in the long-term. [Submitted: 22 April 2021; Accepted: 29 December 2021] Journal: European J. of Industrial Engineering Pages: 60-89 Issue: 1 Volume: 17 Year: 2023 Keywords: lean; lean manufacturing; sustainability; multi-method research; continuous improvement. File-URL: http://www.inderscience.com/link.php?id=127740 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:1:p:60-89 Template-Type: ReDIF-Article 1.0 Author-Name: Orhan Karasakal Author-X-Name-First: Orhan Author-X-Name-Last: Karasakal Author-Name: Esra Karasakal Author-X-Name-First: Esra Author-X-Name-Last: Karasakal Author-Name: Özgün Töreyen Author-X-Name-First: Özgün Author-X-Name-Last: Töreyen Title: A partial coverage hierarchical location allocation model for health services Abstract: We consider a hierarchical maximal covering location problem (HMCLP) to locate health centres and hospitals so that the maximum demand is covered by two levels of services in a successively inclusive hierarchy. We extend the HMCLP by introducing the partial coverage and a new definition of the referral. The proposed model may enable an informed decision on the healthcare system when dynamic adaptation is required, such as a COVID-19 pandemic. We define the referral as coverage of health centres by hospitals. A hospital may also cover demand through referral. The proposed model is solved optimally for small problems. For large problems, we propose a customised genetic algorithm. Computational study shows that the GA performs well, and the partial coverage substantially affects the optimal solutions. [Submitted: 20 January 2021; Accepted: 15 January 2022] Journal: European J. of Industrial Engineering Pages: 115-147 Issue: 1 Volume: 17 Year: 2023 Keywords: hierarchical maximal covering location problem; partial coverage; gradual coverage; referral; heuristics; genetic algorithm. File-URL: http://www.inderscience.com/link.php?id=127742 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:17:y:2023:i:1:p:115-147