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European Journal of Industrial Engineering

European Journal of Industrial Engineering (EJIE)

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European J. of Industrial Engineering (32 papers in press)

Regular Issues

  • The impact of online sales in centralized and decentralized dual-channel supply chains   Order a copy of this article
    by Subrata Saha 
    Abstract: This paper studies a supply chain structure featuring two different types of distribution channels through which manufacturers sell products. The centralised and decentralised distribution channels considered in this study are affected by online sales outside the structured channels. In the centralised distribution channel, two retail stores located in geographically distinct markets are operated by a single owner. In the decentralised distribution channel, two retailers independently operate two retail stores. In the non-cooperative scenario, the manufacturer always prefers the decentralised distribution channel irrespective of whether an online channel is used. To achieve channel coordination, a revenue-sharing contract is applied, but it can be used to coordinate only the decentralised distribution system. Therefore, a modified revenue-sharing contract is proposed to coordinate the centralised distribution system. The analytical study reveals that without coordination among the channel members, the manufacturer always earns maximum profit in decentralised distribution systems. However, if the supply chain is coordinated, then the manufacturer receives more benefits from using the centralised distribution systems under certain conditions. Propositions are presented to describe the characteristics of distribution structures, and to provide meaningful management guidelines for coordinating them. Extensive numerical investigations are also presented.
    Keywords: Supply chain management; Dual-channel supply chain; Revenue sharing contract; Pricing strategy; Stackelberg.
    DOI: 10.1504/EJIE.2018.10011153
     
  • Risk-Averse Joint Facility Location-Inventory Optimization for Green Closed-Loop Supply   Order a copy of this article
    by Guodong Yu, Pengcheng Dong, Ying Xu, Xiao Zhao 
    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 01 mixed-integer nonlinear stochastic programming to minimise the total expected cost and CO2 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.
    Keywords: green closed-loop supply chain; facility location; inventory; risk-averse; chance constraint; distributionally robust optimisation.
    DOI: 10.1504/EJIE.2023.10046132
     
  • A stochastic mixed-integer model to support foodbank resources prepositioning during the prelude to a natural disaster   Order a copy of this article
    by ADRIAN RIVERA, Neale Smith, Esteban Ogazon, Angel Ruiz Bartolome 
    Abstract: A key strategic issue in pre-disaster planning for humanitarian logistics is the pre-establishment of adequate capacity and resources that enable ef?cient 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. [Received: 19 October 2021; Revised: 24 February 2022]
    Keywords: humanitarian logistics; HL; foodbanks; natural disasters; optimisation; scenarios; stochastic.
    DOI: 10.1504/EJIE.2023.10045985
     
  • A survey on network design problems: main variants and resolution approaches   Order a copy of this article
    by Imen Mejri, Safa Bhar Layeb, Farah Zeghal 
    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, NDPs pose significant algorithmic challenges, as they are notoriously NP-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 NDPs 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 NDPs are derived.
    Keywords: network design problems; NDPs; literature review; survey; combinatorial optimisation.
    DOI: 10.1504/EJIE.2022.10046171
     
  • An optimal supplier selection method for uncertain sustainable supply chains   Order a copy of this article
    by Qiurui Liu, He Huang, Ziqiang Zeng, Lin Chen, Junren Ming 
    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, 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 transportation 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. [Received: 25 October 2021; Accepted: 24 February 2022]
    Keywords: sustainable supply chain; supplier selection; performance optimisation; decision-making model.
    DOI: 10.1504/EJIE.2023.10046289
     
  • Data-driven imitation learning-based approach for order size determination in supply chains   Order a copy of this article
    by Dony S. Kurian, V. Madhusudanan Pillai, J. Gautham, Akash Raut 
    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
    Keywords: supply chain; order size determination; machine learning; behavioural experiments; LightGBM; imitation learning; beer game.
    DOI: 10.1504/EJIE.2023.10046611
     
  • A survey on network design problems: main variants and resolution approaches   Order a copy of this article
    by Imen MEJRI, SAFA BHAR LAYEB, Farah ZEGHAL 
    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, NDPs pose significant algorithmic challenges, as they are notoriously NP-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 NDPs 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 NDPs are derived. [Received: 14 March 2021; Accepted: 23 January 2022]
    Keywords: network design problems; NDPs; literature review; survey; combinatorial optimisation.
    DOI: 10.1504/EJIE.2023.10046647
     
  • Risk-Averse Joint Facility Location-Inventory Optimization for Green Closed-Loop Supply Chain Network Design under Demand Uncertainty   Order a copy of this article
    by Ying Xu, Xiao Zhao, Pengcheng Dong, Guodong YU 
    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
    Keywords: green closed-loop supply chain; facility location; inventory; risk-averse; chance constraint; distributionally robust optimisation.
    DOI: 10.1504/EJIE.2023.10046657
     
  • A new framework for balancing and performance evaluation in stochastic assembly line using queueing networks   Order a copy of this article
    by MEHMET PINARBA?I, Mustafa Yüzük?rm?z? 
    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. [Received: 10 July 2021; Accepted: 19 January 2022]
    Keywords: stochastic assembly line balancing; variability; queueing network; constraint programming; decomposition; simulation.
    DOI: 10.1504/EJIE.2023.10046725
     
  • Robust Estimation of the Process Dispersion for Standard Deviation Control Charts   Order a copy of this article
    by Shih-Chou Kao 
    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]
    Keywords: average run length; ARL; mean squared error; MSE; scale A estimator; trimming; weight function.
    DOI: 10.1504/EJIE.2023.10046746
     
  • Optimizing Green Vehicle Routing Problem-A Real Case Study   Order a copy of this article
    by Dalila Tayachi, Cheima Jendoubi 
    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]
    Keywords: fuel consumption; green vehicle routing problem; iterated local search; logistics; set-partitioning problem.
    DOI: 10.1504/EJIE.2023.10047815
     
  • Coordination Strategies of Dual Channel Closed-loop Supply Chain Considering Demand Disruptions   Order a copy of this article
    by Di Wu, Peng Li, Juhong Chen, Hao Wang 
    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
    Keywords: demand disruptions; dual channel closed-loop supply chain; recovery rate; pricing strategies; coordination strategies.
    DOI: 10.1504/EJIE.2023.10048025
     
  • Location-inventory-reliability optimisation problem in a multi-objective multi-period three-level supply chain network with stochastic demand   Order a copy of this article
    by Farid Abdi, Hiwa Farughi, Heibatolah Sadeghi, Jamal Arkat 
    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. [Received: 9 September 2021; Accepted: 9 March 2022]
    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.
    DOI: 10.1504/EJIE.2022.10049686
     
  • A novel QFD-based analytical guideline approach for painting applicator nozzle selection   Order a copy of this article
    by Gustavo Franco Barbosa, Pedro Henrique Da Silva Guedes, Sidney Bruce Shiki, Iris Bento Da Silva, Guylherme Emmanuel Tagliaferro De Queiroz 
    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. [Received: 14 June 2021; Accepted: 3 July 2022]
    Keywords: quality function deployment; QFD; analytical guideline; decision process; painting; manufacturing.
    DOI: 10.1504/EJIE.2022.10049777
     
  • Third-party remanufacturing modes with integrated tax-subsidy policy   Order a copy of this article
    by Zhangwei Feng, Na Luo, Bisheng Du, Haorui Wang 
    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. [Received: 8 September 2021; Accepted: 17 July 2022]
    Keywords: outsourcing; authorisation; product quality; green consumer preference; integrated tax-subsidy; game theory.
    DOI: 10.1504/EJIE.2023.10050299
     
  • An auction mechanism for capacity allocation in identical parallel machines with time window constraints   Order a copy of this article
    by Qianqian Zhu, Xiuli Wang 
    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]
    Keywords: capacity allocation; auction mechanism; price discrimination; Lagrangian relaxation.
    DOI: 10.1504/EJIE.2023.10050357
     
  • Efficient Hierarchical Hybrid Delivery in the Last Mile Logistics   Order a copy of this article
    by Ardavan Babaei, Majid Khedmati, Mohammad Reza Akbari Jokar 
    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.
    Keywords: last-mile delivery; customer behaviour data; delivery options; hierarchical; efficient; supply chain.
    DOI: 10.1504/EJIE.2023.10050962
     
  • Decision-making and sub-coordination in a newsvendor model with a third party logistics service provider   Order a copy of this article
    by Lin Jiang, Dongmei Liu, Shuaihui Tian 
    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]
    Keywords: newsvendor; logistics service provider; outsourcing; sub-coordination.
    DOI: 10.1504/EJIE.2024.10051044
     
  • A Collaborative Model for Predictive Maintenance of After-Sales Equipment Based on Digital Twin   Order a copy of this article
    by Xiao Li, Hongfei Liang, Yuchen Chen, Yuanpeng Ruan, Lei Wang 
    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]
    Keywords: digital twin; predictive maintenance; collaborative maintenance; hidden semi-Markov chain model; after-sales equipment.
    DOI: 10.1504/EJIE.2023.10051066
     
  • Inter-cell scheduling based on a transportation vehicle sharing strategy   Order a copy of this article
    by Qiong Liu, Qin Ye, Xu Mei, Qiang Zhang 
    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]
    Keywords: cellular manufacturing; inter-cell scheduling; multi-objective optimisation; shuffled frog leaping algorithm; SFLA; current transportation strategy; CTS; transportation vehicle sharing strategy.
    DOI: 10.1504/EJIE.2024.10051440
     
  • Processes-oriented maturity framework for Lean Manufacturing with health-at-work and performance management objectives   Order a copy of this article
    by Gilles Galichet, Roberta COSTA AFFONSO, Vincent Cheutet 
    Abstract: Lean manufacturing is recognised as an approach that improves companies’ performance through the elimination of non-value-added activities. However, not all companies implement this approach since there is no standard method for doing so, and some authors have even identified it as a source of stress or occupational illnesses. In light of this, how can an action plan, for its implementation, be defined while guaranteeing the synergy between industrial performance and health at work? Maturity frameworks are tools that identify a company’s level of capability regarding the studied parameters, and so can serve as a guide in their organisational transformation. In this article we propose a process-oriented maturity framework for lean manufacturing transformation that considers health at work and the company’s managerial and operational performance. The framework is illustrated through a company’s evolution over the course of a five-year project, and is then discussed. [Submitted: 14 June 2021; Accepted: 19 September 2022]
    Keywords: health at work; industrial performance; maturity; organisational transformation; capability; lean manufacturing.
    DOI: 10.1504/EJIE.2024.10051586
     
  • Service variety strategies for healthcare systems under capacity limitations   Order a copy of this article
    by Lu Chen, Yi Xia, Jiajia Zhu, Junyi Li 
    Abstract: Some hospitals provide paid medical services in addition to basic medical services. Although paid medical services can provide a better experience for patients who are highly sensitive to delays, they cause a capacity reduction in basic medical services. We develop a model incorporating product line design and queuing models to determine the service capacity allocation for a healthcare system. Patients are categorised into two segments according to their sensitivities to waiting time. We derive the optimal capacity allocations under two strategies (providing both paid and basic medical services and providing only the basic one) and compare them. Results show that the hospital should provide only the basic medical service even if high-sensitive patients are extremely sensitive to waiting time. Under certain conditions, a hospital providing differentiated medical services should decrease capacity allocation to the paid service even if high-sensitive patients are extremely sensitive to waiting time. [Submitted: 13 April 2022; Accepted: 22 September 2022]
    Keywords: healthcare system; capacity limitation; product line design; queuing model.
    DOI: 10.1504/EJIE.2024.10051678
     
  • Implementing a Bivariate Preventive Maintenance Strategy for Stochastically Deteriorating Systems with Two Types of Shocks   Order a copy of this article
    by Jun Chang, Wenjie Dong, Zhigeng Fang 
    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 mutual 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. [Received: 14 October 2021; Accepted: 2 January 2022]
    Keywords: degradation modelling; random shocks; mutual dependence; two types of shocks; preventive maintenance.
    DOI: 10.1504/EJIE.2023.10051715
     
  • Operational strategies of fuzzy inventory models for costly metallic items with conditional trade-credit policy linked to the purchasing cost   Order a copy of this article
    by Bappa Mondal, Arindam Garai, Tapan Kumar Roy 
    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 ?-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. [Received: 26 April 2020; Accepted: 3 July 2022]
    Keywords: inventory model; conditional trade-credit; accumulated fund; partial back-ordering; costly metallic item; volatile market.
    DOI: 10.1504/EJIE.2023.10051764
     
  • Two-Machine Flowshop Scheduling with Fuzzy Processing Times and Flexible Operations   Order a copy of this article
    by Zeynep Uruk, Ayten Y?lmaz Yalç?ner 
    Abstract: This paper considers a two-machine flowshop scheduling problem with fuzzy processing times and flexible operations to minimise makespan. The jobs have three operations, one of which is a flexible operation that can be processed on one of the machines. The flexible operation should be assigned to one of the machines. Moreover, the processing times on the machines are not fixed but fuzzy processing times which are assumed to have triangular possibility distributions. Firstly, a possibilistic mathematical model is proposed with fuzzy processing times and then it is converted to an auxiliary crisp model using the weighted average defuzzification method. For the large cases where the exact algorithm may not be efficient, a heuristic algorithm is proposed. [Submitted: 24 May 2022; Accepted: 18 October 2022]
    Keywords: scheduling; flowshop; makespan; fuzzy processing times; flexible operations.
    DOI: 10.1504/EJIE.2024.10052125
     
  • Operations Research Applied to Aerospace Manufacturing and Assembly: A survey   Order a copy of this article
    by Bruno Silva, Reinaldo Morabito 
    Abstract: This paper presents an overview of operations research approaches applied to aerospace manufacturing and assembly. A survey was carried out in the main literature databases and 70 related works were found, revealing a notable growth in the number of papers in the 2010s. For the purposes of this study, aerospace industrial operations were classified into three main stages, namely manufacturing, structural and final assembly and the papers, methods and results of each stage are presented and analysed, synthesising the main applications and techniques used. Finally, a conceptual diagram of this review is presented and a synthesis of opportunities is provided for future research in this industry. [Received 31 January 2021; Accepted 19 September 2022]
    Keywords: aerospace manufacturing and assembly; survey; operations research; aerospace industry; Industry 4.0.
    DOI: 10.1504/EJIE.2024.10052262
     
  • An integrated Markov chain model for the economic-statistical design of adaptive multivariate control charts and maintenance planning   Order a copy of this article
    by Jalal Taji, Hiwa Farughi, Hasan Rasay 
    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 (Vp) 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 ARL0 and ARL1 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]
    Keywords: integrated model; quality control; chi-square control chart; maintenance planning.
    DOI: 10.1504/EJIE.2023.10044732
     
  • Solving airline crew pairing problems through constraint partitioning   Order a copy of this article
    by Maryam Radman, Kourosh Eshghi 
    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]
    Keywords: crew pairing problems; CPPs; constraint partitioning; decomposition technique; sub-problem; airline industry.
    DOI: 10.1504/EJIE.2023.10044607
     
  • Critical factors for sustaining lean manufacturing in the long-term: a multi-method study   Order a copy of this article
    by Natalia Roberta Lopes, Moacir Godinho Filho, Gilberto Miller Devós Ganga, Guilherme Luz Tortorella, Mario Henrique Bueno Moreira Callefi, Bruna Tamara De Lima 
    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]
    Keywords: lean; lean manufacturing; sustainability; multi-method research; continuous improvement.
    DOI: 10.1504/EJIE.2023.10045201
     
  • Conditional design of the Shewhart chart with unknown process parameters based on median run length   Order a copy of this article
    by XueLong Hu, Philippe Castagliola, AnAn Tang, XiaoJian Zhou 
    Abstract: Numerous researches have been done on the Shewhart chart based on the average run length (ARL) metric. Since the shape of the run length (RL) distribution changes with the mean shift size, the median run length (MRL) is argued to be a better criterion for evaluating the performance of the Shewhart chart. Moreover, when the process parameters are unknown, the phase 2 properties of the Shewhart 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 MRL values, both the average MRL (AMRL) and the standard deviation of MRL (SDMRL) will be used together in our article. The performance analyses of the MRL-based Shewhart chart are provided. To prevent too many lower in-control MRL 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 MRL values of the Shewhart chart. [Submitted: 26 September 2018; Accepted: 15 January 2022]
    Keywords: Shewhart chart; median run length; estimated parameters; average median run length; Standard deviation of median run length.
    DOI: 10.1504/EJIE.2023.10049858
     
  • A partial coverage hierarchical location allocation model for health services   Order a copy of this article
    by Orhan Karasakal, Esra Karasakal, Özgün Töreyen 
    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]
    Keywords: hierarchical maximal covering location problem; partial coverage; gradual coverage; referral; heuristics; genetic algorithm.
    DOI: 10.1504/EJIE.2023.10045477
     
  • Searching for the best profit-sharing allocation in multi-echelon supply chain   Order a copy of this article
    by Nguyen Van Hop 
    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]
    Keywords: supply chain coordination; profit sharing; multi-echelon supply chain.
    DOI: 10.1504/EJIE.2023.10046732