Template-Type: ReDIF-Article 1.0 Author-Name: Vasilis P. Koutras Author-X-Name-First: Vasilis P. Author-X-Name-Last: Koutras Author-Name: Sonia Malefaki Author-X-Name-First: Sonia Author-X-Name-Last: Malefaki Author-Name: Agapios N. Platis Author-X-Name-First: Agapios N. Author-X-Name-Last: Platis Title: Opportunistic maintenance on the automatic switching mechanism of a two-unit multi-state system Abstract: A two-unit multi-state deteriorating system consisting of one operating and one unit in standby mode, under preventive maintenance and imperfect switch is considered. System control is switched to the standby unit upon operating unit failure or maintenance, either automatically, by an automatic switching mechanism (ASM), or manually. To avoid ASM failures, triggering an opportunistic maintenance (OM) on the automatic switching mechanism is proposed upon unit maintenance. The main objective is to evaluate the effect of ASM opportunistic maintenance on system's dependability and performance. The asymptotic availability and the total expected operational cost of the system with and without automatic switching mechanism OM for various unit maintenance policies are compared through a numerical example. The results are encouraging since the proposed model with OM provides higher availability and significantly reduced operational cost regardless the adopted maintenance policy. [Received: 29 January 2020; Accepted: 28 September 2020] Journal: European J. of Industrial Engineering Pages: 616-642 Issue: 5 Volume: 15 Year: 2021 Keywords: opportunistic maintenance; multi-state deteriorating system; imperfect switch; redundancy; asymptotic availability; total expected operational cost. File-URL: http://www.inderscience.com/link.php?id=117319 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:5:p:616-642 Template-Type: ReDIF-Article 1.0 Author-Name: Fadwa Oukhay Author-X-Name-First: Fadwa Author-X-Name-Last: Oukhay Author-Name: Ahmed Badreddine Author-X-Name-First: Ahmed Author-X-Name-Last: Badreddine Author-Name: Taieb Ben Romdhane Author-X-Name-First: Taieb Ben Author-X-Name-Last: Romdhane Title: Towards a new knowledge-based framework for integrated quality control planning Abstract: This paper presents a new knowledge-based framework for integrated quality control planning. The proposed approach is based on the concepts of advanced product quality planning (APQP) and employs the quality function deployment (QFD) for the selection of the features to be controlled. Accordingly, APQP/QFD related issues are addressed, namely the uncertainty in the customer's voice deployment, the complexity of causal interrelationships analysis, and the difficulties of knowledge exploitation. A new QFD model based on fuzzy cognitive map (FCM) and Choquet integral is thus proposed. FCM development allows the capture and modelling of product/process causality. The FCM simulation assesses the impacts of the product, parts, and process characteristics on the customer requirements (CRs). Choquet integral is used for the aggregation of these impacts in order to deal with the interactions between CRs. The effectiveness of this approach is evaluated by the results of an experimental case study. [Received: 26 April 2019; Accepted: 10 September 2020] Journal: European J. of Industrial Engineering Pages: 583-615 Issue: 5 Volume: 15 Year: 2021 Keywords: product and process quality control planning; quality function deployment; QFD; fuzzy cognitive map; FCM; Choquet integral. File-URL: http://www.inderscience.com/link.php?id=117324 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:5:p:583-615 Template-Type: ReDIF-Article 1.0 Author-Name: Asma Ladj Author-X-Name-First: Asma Author-X-Name-Last: Ladj Author-Name: Fatima Benbouzid-Si Tayeb Author-X-Name-First: Fatima Benbouzid-Si Author-X-Name-Last: Tayeb Author-Name: Christophe Varnier Author-X-Name-First: Christophe Author-X-Name-Last: Varnier Title: Hybrid of metaheuristic approaches and fuzzy logic for the integrated flowshop scheduling with predictive maintenance problem under uncertainties Abstract: Maintenance interventions must be properly integrated in the production scheduling in order to prevent failure risks. In this context, we investigate the permutation flowshop scheduling problem subjected to predictive maintenance based on prognostics and health management (PHM). To solve this problem, two integrated metaheuristics are proposed with the objective of minimising the makespan: a carefully tailored genetic algorithm (GA), and a variable neighbourhood search (VNS) incorporating well designed local search procedures. Moreover, we hybridise the two metaheuristics where the GA best solution is introduced as initial solution of VNS. The proposed metaheuristics use the fuzzy logic framework to deal with the uncertainties. To gain insight in the performance of the proposed methods, several computational experiments were conducted against Taillard's benchmarks endowed with the prognostics and predictive maintenance data. The results show a clear superiority of the proposed algorithms, especially for the genetic algorithm, regarding both solution quality and computational times. [Received: 10 June 2019; Accepted: 27 October 2020] Journal: European J. of Industrial Engineering Pages: 675-710 Issue: 5 Volume: 15 Year: 2021 Keywords: permutation flowshop scheduling problem; PFSP; predictive maintenance; post prognostic decision; PPD; variable neighbourhood search; VNS; genetic algorithm; fuzzy logic. File-URL: http://www.inderscience.com/link.php?id=117325 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:5:p:675-710 Template-Type: ReDIF-Article 1.0 Author-Name: Wassim Zahrouni Author-X-Name-First: Wassim Author-X-Name-Last: Zahrouni Author-Name: Hichem Kamoun Author-X-Name-First: Hichem Author-X-Name-Last: Kamoun Title: Scheduling in robotic cells with time window constraints Abstract: This paper addresses the cyclic scheduling problem arising in two and three-machine robotic cells with time window constraints where multiple part-types are produced. Due to its complexity, very few studies have tackled the problem. Previous researches were generally limited to single or at most to two part-types where the associated part sequencing problem vanishes since the production is cyclic. We proved that the two-machine problem could be apprehended as a travelling salesman problem. For the three-machine case, we proposed a heuristic aimed at finding the sequence of robot activities and the sequence of parts that jointly minimises the cycle time in a special class of cycles. A lower bound is also provided, and computational results are reported. [Received: 18 October 2018; Revised: 22 January 2020; Accepted: 14 March 2020] Journal: European J. of Industrial Engineering Pages: 206-225 Issue: 2 Volume: 15 Year: 2021 Keywords: hoist scheduling problem; HSP; robotic cells; time window constraints; cyclic scheduling; sequencing. File-URL: http://www.inderscience.com/link.php?id=114001 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:2:p:206-225 Template-Type: ReDIF-Article 1.0 Author-Name: Seong Wook Hwang Author-X-Name-First: Seong Wook Author-X-Name-Last: Hwang Author-Name: Seokgi Lee Author-X-Name-First: Seokgi Author-X-Name-Last: Lee Author-Name: Sang Jin Kweon Author-X-Name-First: Sang Jin Author-X-Name-Last: Kweon Title: An integrated inventory and distribution problem for alternative fuel: a matheuristic approach Abstract: Due to the limited driving range of alternative fuel (AF) vehicles and their immature refueling infrastructure, a successful transition to the era of AF vehicles necessitates ensuring stable supply and management of AF in the refueling network. This paper proposes a new mathematical framework to solve an AF inventory and distribution problem in which an AF provider manages and operates the AF refueling network to meet all AF demand in a given time horizon. As a solution method, we present a mixed-integer programming (MIP) model that minimises the sum of AF service, inventory holding, and distribution costs. Furthermore, a matheuristic algorithm hybridising an MIP model and an adaptive large neighbourhood search algorithm is designed to solve practical problems of real transportation networks. The proposed matheuristic algorithm is validated with an application to small-size instances and is applied to six states in the USA with real traffic flows. [Received: 18 September 2019; Accepted: 6 November 2020] Journal: European J. of Industrial Engineering Pages: 711-744 Issue: 5 Volume: 15 Year: 2021 Keywords: alternative fuel vehicle; refueling service; inventory routing problem; mixed-integer programming; MIP; adaptive large neighbourhood search; ALNS. File-URL: http://www.inderscience.com/link.php?id=117331 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:5:p:711-744 Template-Type: ReDIF-Article 1.0 Author-Name: João N.C. Gonçalves Author-X-Name-First: João N.C. Author-X-Name-Last: Gonçalves Author-Name: Paulo Cortez Author-X-Name-First: Paulo Author-X-Name-Last: Cortez Author-Name: M. Sameiro Carvalho Author-X-Name-First: M. Sameiro Author-X-Name-Last: Carvalho Title: K-means clustering combined with principal component analysis for material profiling in automotive supply chains Abstract: At a time where available data is rapidly increasing in both volume and variety, descriptive data mining (DM) can be an important tool to support meaningful decision-making processes in dynamic supply chain (SC) contexts. Up until now, however, scarce attention has been given to the application of DM techniques in the field of inventory management. Here, we take advantage of descriptive DM to detect and grasp important patterns among several features that coexist in a real-world automotive SC. Principal component analysis (PCA) is employed to analyse and understand the interrelations between ten quantitative and dependent variables in a multi-item/multi-supplier environment. Afterwards, the principal component scores are characterised via a K-means clustering, allowing us to classify the samples into four clusters and to derive different profiles for the multiple inventory items. This work provides evidence that descriptive DM contributes to find interesting feature-patterns, resulting in the identification of important risk profiles that may effectively leverage inventory management for improved SC performance. [Received: 5 April 2019; Revised: 1 December 2019; Revised: 22 January 2020; Accepted: 21 April 2020] Journal: European J. of Industrial Engineering Pages: 273-294 Issue: 2 Volume: 15 Year: 2021 Keywords: supply chain; data mining; K-means clustering; principal component analysis; PCA. File-URL: http://www.inderscience.com/link.php?id=114009 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:2:p:273-294 Template-Type: ReDIF-Article 1.0 Author-Name: Majid Esmaelian Author-X-Name-First: Majid Author-X-Name-Last: Esmaelian Author-Name: Ahmad Sobhani Author-X-Name-First: Ahmad Author-X-Name-Last: Sobhani Author-Name: Hadi Shahmoradi Author-X-Name-First: Hadi Author-X-Name-Last: Shahmoradi Author-Name: Milad Mohammadi Author-X-Name-First: Milad Author-X-Name-Last: Mohammadi Title: Scheduling the capacitated identical parallel machines problem: a new formulation with sequence-dependent setup costs and different due dates Abstract: This paper schedules capacitated parallel machines of a real production system by considering different quantities of production and processing times required to complete customer orders. A new mixed linear programming model is developed according to the concept of constrained vehicle routing problems to have a complete schedule for machines by determining the sequence of both jobs and idle times for each machine. The optimisation model minimises the total cost of the production system, including tardiness, earliness and sequence-dependent setup costs. A constraint programming (CP) model and a meta-heuristic hybrid algorithm are also developed to compare their results with the mixed linear programming model. The numerical findings show that the total cost estimated by the mixed integer programming model is 10%-13% better (lower) than the ones estimated by the CP model and the meta-heuristic algorithm when small instances of the scheduling problem are solved. By increasing the size of the scheduling problem, the meta-heuristic algorithm shows the best computational performance estimating 11% better (lower) total cost compared with the CP model. [Received: 14 April 2020; Accepted: 26 October 2020] Journal: European J. of Industrial Engineering Pages: 643-674 Issue: 5 Volume: 15 Year: 2021 Keywords: capacitated identical parallel machines; constrained vehicle routing problem; mixed integer linear programming; constraint programming; meta-heuristic algorithm. File-URL: http://www.inderscience.com/link.php?id=117337 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:5:p:643-674 Template-Type: ReDIF-Article 1.0 Author-Name: Rung-Hung Su Author-X-Name-First: Rung-Hung Author-X-Name-Last: Su Author-Name: Chia-Huang Wu Author-X-Name-First: Chia-Huang Author-X-Name-Last: Wu Author-Name: Dong-Yuh Yang Author-X-Name-First: Dong-Yuh Author-X-Name-Last: Yang Title: Conservative profitability evaluation for a newsboy-type product based on achievable capacity index Abstract: The achievable capacity index (ACI) can measure the profitability of a newsboy-type product with probabilistic distributed demand. This criterion has been employed to deal with the problem of profitability evaluation by implementing statistical hypothesis testing. However, due to sampling errors, the point estimate of ACI probably overestimates the profitability. To this end, we derive a lower confidence bound of ACI (LCBA) to give a conservative evaluation of profitability. Since the complex sampling distribution of ACI makes it difficult to obtain an explicit closed-form expression of LCBA, we characterise the relationship between LCBA and estimator of ACI under given confidence level and sample size. A computational algorithm is proposed to obtain LCBA. Extensive numerical results of LCBA for various sample sizes, confidence levels and estimates are tabulated. Finally, we illustrate the practicality and applicability of the proposed method in an application example. Some managerial insights are also discussed. [Received: 21 May 2019; Accepted: 7 April 2020] Journal: European J. of Industrial Engineering Pages: 250-272 Issue: 2 Volume: 15 Year: 2021 Keywords: achievable capacity index; ACI; conservative profitability evaluation; lower confidence bound; newsboy problem. File-URL: http://www.inderscience.com/link.php?id=114014 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:2:p:250-272 Template-Type: ReDIF-Article 1.0 Author-Name: Anny Del Mar Agamez-Arias Author-X-Name-First: Anny Del Mar Author-X-Name-Last: Agamez-Arias Author-Name: José P. García-Sabater Author-X-Name-First: José P. Author-X-Name-Last: García-Sabater Author-Name: Angel Ruiz Author-X-Name-First: Angel Author-X-Name-Last: Ruiz Author-Name: José Moyano-Fuentes Author-X-Name-First: José Author-X-Name-Last: Moyano-Fuentes Title: A systematic literature review of the design of intermodal freight transportation networks addressing location-allocation decisions Abstract: This systematic literature review focuses on planning models jointly addressing location and allocation decisions related to the design of intermodal freight transportation networks. Since this body of literature is evolving quickly, a methodology based on a linked two-stage analysis is proposed. The first stage analyses recent surveys to establish the guidelines and criteria that enable the subsequent systematic review. Then, the review concentrates on analysing contributions to the current state of the art on intermodal freight transportation from two close, yet different research streams: transportation networks and supply chain networks. Key features identified in the first stage such as: 1) the research problem's characteristics; 2) the intermodal networks design's particularities; 3) proposed solution techniques, among others, are used to classify and analyse the different contributions. The review identifies current trends, emerging topics and some issues that merit being researched. [Received: 4 May 2019; Revised: 12 December 2019; Accepted: 1 February 2020] Journal: European J. of Industrial Engineering Pages: 1-34 Issue: 1 Volume: 15 Year: 2021 Keywords: systematic literature review; SLR; intermodal facilities; network design; location-allocation problem; intermodal freight transport; mathematical programming; modelling; optimisation techniques. File-URL: http://www.inderscience.com/link.php?id=113506 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:1:p:1-34 Template-Type: ReDIF-Article 1.0 Author-Name: Qi Cao Author-X-Name-First: Qi Author-X-Name-Last: Cao Author-Name: K.M. Leung Author-X-Name-First: K.M. Author-X-Name-Last: Leung Author-Name: Wenhua Hou Author-X-Name-First: Wenhua Author-X-Name-Last: Hou Title: Two-phase differential evolution for solving emergency response supplies optimisation problem Abstract: A material supply model is constructed for serious disasters in which a large number of supply centres and disaster areas are involved. We introduce a new method referred to as two-phase differential evolution (TPDE) to solve this kind of complex nonlinear programming problem. In constraint handling phase, the goal is to explore the parameter space to identify a feasible solution quickly. In optimum seeking phase, the aim is to gradually improve the quality of current best solution. Different differential evolution schemes and special handling techniques are utilised in the two phases. Extensive numerical optimisation experiments are conducted where TPDE is compared with results obtained from using commercial software and three evolutionary optimisation methods. We determine that TPDE is always able to find a feasible solution with fewer generations and the optimal solution almost always ranks as the best. This work is beneficial to address large-scale nonlinear optimisation problems with constraints. [Received: 28 August 2019; Revised: 1 February 2020; Accepted: 8 March 2020] Journal: European J. of Industrial Engineering Pages: 103-130 Issue: 1 Volume: 15 Year: 2021 Keywords: evolutionary computation; large-scale optimisation; emergency logistics; differential evolution; material supply model; two-phase optimisation. File-URL: http://www.inderscience.com/link.php?id=113507 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:1:p:103-130 Template-Type: ReDIF-Article 1.0 Author-Name: Ali Sayyah Author-X-Name-First: Ali Author-X-Name-Last: Sayyah Author-Name: Amin Abbasi-Pooya Author-X-Name-First: Amin Author-X-Name-Last: Abbasi-Pooya Author-Name: Reza Baradaran Kazemzadeh Author-X-Name-First: Reza Baradaran Author-X-Name-Last: Kazemzadeh Title: A new multi-objective-multi-criteria model for determining physical asset management strategy based on maintenance and procurement factors Abstract: In this research, a new multi-objective-multi-criteria model is presented to determine physical asset management strategy for capital equipment. Initially, a multi-objective model is formulated to determine non-dominated strategies considering cost, reliability, and availability as objective functions. Secondly, the strategies will be ranked based on decision maker preferences and restrictions using a PROMETHEE-entropy module. Each strategy is a vector of procurement variables (dealer-manufacturer and contract type) and maintenance planning variables (<i>PM action level, PM interval and the degree of upgrade action</i>). The multi-objective model, which is a new nonlinear mixed integer optimisation model, is solved using a customised NSGA-II. Buy, lease, rent and upgrading a used equipment are contract types that are considered. The model is used in a real case for determination of asset management strategy for a truck to be used in a mine for 48 months. A piece of software is designed for simplification of using the model. [Received: 13 January 2019; Accepted: 3 March 2020] Journal: European J. of Industrial Engineering Pages: 167-205 Issue: 2 Volume: 15 Year: 2021 Keywords: physical asset management; PAM; maintenance planning; contract management; reliability; availability; equipment management. File-URL: http://www.inderscience.com/link.php?id=114019 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:2:p:167-205 Template-Type: ReDIF-Article 1.0 Author-Name: Ertan Yakıcı Author-X-Name-First: Ertan Author-X-Name-Last: Yakıcı Author-Name: Mumtaz Karatas Author-X-Name-First: Mumtaz Author-X-Name-Last: Karatas Author-Name: Serhan Duran Author-X-Name-First: Serhan Author-X-Name-Last: Duran Title: A multi-objective approach in expanding the pre-positioning warehouse networks in humanitarian logistics Abstract: In this study, we focus on the structure of the pre-positioning warehouse networks which have a great effect on the response to a disaster. We determine the pre-positioning warehouse network configuration of CARE International with a multi-objective approach using the recent decade data. In addition to the minimisation of the average response time of an item, we also consider the maximum response time and maximum water delivery time as additional objectives. After analysis of the non-dominated solutions, we conclude that CARE International should open a warehouse in Kenya and pre-position 39%-44% of all relief items other than tents to this location while starting to operate the Denmark warehouse instead of the Dubai warehouse. [Received: 20 March 2018; Revised: 12 September 2019; Accepted: 26 February 2020] Journal: European J. of Industrial Engineering Pages: 67-102 Issue: 1 Volume: 15 Year: 2021 Keywords: pre-positioning; humanitarian relief logistics; warehouse location; network expansion; multi-objective. File-URL: http://www.inderscience.com/link.php?id=113508 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:1:p:67-102 Template-Type: ReDIF-Article 1.0 Author-Name: Qing-Mi Hu Author-X-Name-First: Qing-Mi Author-X-Name-Last: Hu Title: Hub location problem with balanced round-trip flows on hub links Abstract: This paper addresses the classical single and multiple allocation hub location problems with fully interconnected hubs, in which the balanced round-trip flows on hub links are considered in the strategic decision making process. The use of balanced round-trip flows on hub links is motivated by the need to decrease the empty-trip rate of vehicles and increase the full-load rate of vehicles. Mixed-integer programming models are presented for single and multiple allocation versions of the problems. Numerical experiments with the CAB and AP datasets are performed to analyse the impacts of balanced flows on the network configurations and the utilisation of service resources. Experimental results show that the number of located hubs tends to decrease with a decrease in the allowable unbalanced round-trip degree of the hub link flows. The utilisation rate of transportation resources can be significantly improved with a small increase in the traditional operating cost. Moreover, a better modelling of economies of scale can be achieved when considering balanced flows. [Received: 22 September 2019; Accepted: 15 March 2020] Journal: European J. of Industrial Engineering Pages: 131-166 Issue: 1 Volume: 15 Year: 2021 Keywords: hub location; balanced flows; economies of scale; mixed-integer programming. File-URL: http://www.inderscience.com/link.php?id=113509 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:1:p:131-166 Template-Type: ReDIF-Article 1.0 Author-Name: Weihua Liu Author-X-Name-First: Weihua Author-X-Name-Last: Liu Author-Name: Wanying Wei Author-X-Name-First: Wanying Author-X-Name-Last: Wei Author-Name: Donglei Zhu Author-X-Name-First: Donglei Author-X-Name-Last: Zhu Title: Service capacity procurement in logistics service supply chain with demand updating and reciprocal behaviour Abstract: This paper builds a logistics service supply chain consisting of a logistics service integrator (LSI) and a functional logistics service provider (FLSP), where they collaborate with a reciprocity contract. We aim to analyse the impact of reciprocity on the supply chain members' two-stage service capability procurement decisions under demand updating through a multi-method, combining game theory and a case study. We find that a reciprocity contract could provide a win-win situation and coordinate the supply chain when reciprocity factors are in an appropriate range. Moreover, the reciprocal behaviour of LSI can promote the reduction of wholesale prices, and the reciprocal behaviour of FLSP will increase the purchasing quantity as well as bring forward the purchasing time point of LSI. Lastly, the reciprocal behaviour of both parties is mutually reinforcing; that is, when one party increases its own reciprocity factor, the other party also increases its reciprocity factor as a return. [Received: 30 September 2018; Accepted: 11 February 2020] Journal: European J. of Industrial Engineering Pages: 35-66 Issue: 1 Volume: 15 Year: 2021 Keywords: service capacity procurement; reciprocity contract; demand updating; case study. File-URL: http://www.inderscience.com/link.php?id=113510 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:1:p:35-66 Template-Type: ReDIF-Article 1.0 Author-Name: Solaleh Sadat Kalantari-Kohbanani Author-X-Name-First: Solaleh Sadat Author-X-Name-Last: Kalantari-Kohbanani Author-Name: Maryam Esmaeili Author-X-Name-First: Maryam Author-X-Name-Last: Esmaeili Author-Name: Leopoldo Eduardo Cárdenas-Barrón Author-X-Name-First: Leopoldo Eduardo Author-X-Name-Last: Cárdenas-Barrón Author-Name: Sunil Tiwari Author-X-Name-First: Sunil Author-X-Name-Last: Tiwari Author-Name: Ali Akbar Shaikh Author-X-Name-First: Ali Akbar Author-X-Name-Last: Shaikh Title: A sustainable closed-loop supply chain in a two-period: a game theory approach Abstract: The closed-loop supply chain considers forward and reverse logistics. This paper assumes a two-period setting to demonstrate the interaction and effect of periods on the supply chain. In the first period, the manufacturer acts as a leader which produces new products and sells them to the retailer, and the retailer sells them to customers. In the second period, the manufacturer collects used-products to take profit. The objective of this study is to take care of economic, green, and social issues for both manufacturer and retailer in both periods. It presented a flexible solution method in two phases. A numerical example is presented and solved by applying the proposed solution method. Results indicate that the manufacturer as a leader obtains more profit, whereas the retailer is more sensitive towards the discount rate. Moreover, the retailer's profit is more sensitive to the proportion of returned used products than the manufacturer's profit. [Received: 15 April 2019; Accepted: 15 March 2020] Journal: European J. of Industrial Engineering Pages: 226-249 Issue: 2 Volume: 15 Year: 2021 Keywords: closed-loop supply chain; CLSC; game theory; two-period setting; sustainable. File-URL: http://www.inderscience.com/link.php?id=114030 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:2:p:226-249 Template-Type: ReDIF-Article 1.0 Author-Name: Antoine Clement Author-X-Name-First: Antoine Author-X-Name-Last: Clement Author-Name: Liên Wioland Author-X-Name-First: Liên Author-X-Name-Last: Wioland Author-Name: Virginie Govaere Author-X-Name-First: Virginie Author-X-Name-Last: Govaere Author-Name: Didier Gourc Author-X-Name-First: Didier Author-X-Name-Last: Gourc Author-Name: Julien Cegarra Author-X-Name-First: Julien Author-X-Name-Last: Cegarra Author-Name: François Marmier Author-X-Name-First: François Author-X-Name-Last: Marmier Author-Name: Daouda Kamissoko Author-X-Name-First: Daouda Author-X-Name-Last: Kamissoko Title: Robustness, resilience: typology of definitions through a multidisciplinary structured analysis of the literature Abstract: The concepts of robustness and resilience are used with increasing frequency from different sectors. The literature review reveals several meanings for each of these terms due probably to specific use in each of the sectors and a progressive adjustment of the definitions across time. The aims of this article are to identify these definitions and the main similarities and differences between the concepts of resilience and robustness and to propose a classification in order to avoid confusions, bad meaning and to provide a better understanding of the subtleties under these concepts. Based on a structured analysis of the literature published in journals of different sectors, this paper conceptualises and comprehensively presents a systematic review of the recent literature on the definitions of robustness and resilience. Decision makers and researchers can benefit from our survey since it introduces a structured analysis and recommendations as to which definitions can be used. [Received: 26 February 2020; Accepted: 20 July 2020] Journal: European J. of Industrial Engineering Pages: 487-513 Issue: 4 Volume: 15 Year: 2021 Keywords: structured literature review; definitions; resilience; robustness. File-URL: http://www.inderscience.com/link.php?id=116128 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:4:p:487-513 Template-Type: ReDIF-Article 1.0 Author-Name: Majid Khedmati Author-X-Name-First: Majid Author-X-Name-Last: Khedmati Author-Name: Ardavan Babaei Author-X-Name-First: Ardavan Author-X-Name-Last: Babaei Title: A new DEA model for ranking association rules considering the risk, resilience and decongestion factors Abstract: In this paper, a novel data envelopment analysis (DEA) model is proposed for ranking the association rules. In this regard, a mixed-integer linear programming (MILP) model is proposed to determine the most efficient association rules where, an N-person bargaining game is used to create an interactive competition between the existing N-weights to get a better ranking. In addition, the proposed model is fuzzified by setting the ambiguous threshold of the indicators' weight in each rule to improve the overall ranking of the rules. Finally, the risk, resilience and decongestion factors are also considered to increase the responsiveness of the models to different real-world conditions. The proposed model is validated by some random problems and an illustrative example of market basket analysis where, the proposed model shows better results than the competing models in the literature. In addition, the applicability of the proposed model is illustrated using a real case-study. [Received: 2 February 2020; Accepted: 5 July 2020] Journal: European J. of Industrial Engineering Pages: 463-486 Issue: 4 Volume: 15 Year: 2021 Keywords: ranking association rules; data envelopment analysis; DEA; fuzzy logic; mixed-integer linear programming; MILP; game theory; risk; resilience. File-URL: http://www.inderscience.com/link.php?id=116129 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:4:p:463-486 Template-Type: ReDIF-Article 1.0 Author-Name: Seung-Chul Oh Author-X-Name-First: Seung-Chul Author-X-Name-Last: Oh Author-Name: Hokey Min Author-X-Name-First: Hokey Author-X-Name-Last: Min Author-Name: Young-Hyo Ahn Author-X-Name-First: Young-Hyo Author-X-Name-Last: Ahn Title: Inventory risk pooling strategy for the food distribution network in Korea Abstract: Today's business environments are characterised by the high degree of volatility and risk due to fast changing customer behaviours and increasingly diversified product lines. Since the volatility and risk are often triggered by demand variability, growing efforts are made to control demand variability. One of such efforts includes inventory risk pooling which aims to reduce inventory variability by aggregating customer demand across products, time, and location. The success of inventory risk pooling, however, hinges on its ability to consolidate inventory at the central location of a supply chain network. To help supply chain professionals formulate a wise inventory risk pooling strategy, this paper redesigns a warehouse network in such a way that it increases inventory turnover, reduces the risk of inventory obsolescence/shortage/surplus, allocates inventory to field warehouses closer to highly concentrated customer bases, and centralises inventory stocking locations for the aggregated demand. To solve this complex distribution network redesign problem, we propose a simulation model and test its validity by applying it to an actual distribution problem encountering the consumer packaged goods manufacturer in Korea, which produces and distributes food products. [Received: 14 August 2017; Accepted: 30 June 2020] Journal: European J. of Industrial Engineering Pages: 439-462 Issue: 4 Volume: 15 Year: 2021 Keywords: inventory pooling; distribution network design; processsed food distribution; a cold supply chain; simulation; case study; Korea. File-URL: http://www.inderscience.com/link.php?id=116131 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:4:p:439-462 Template-Type: ReDIF-Article 1.0 Author-Name: Rita Maria Difrancesco Author-X-Name-First: Rita Maria Author-X-Name-Last: Difrancesco Author-Name: Purushottam Meena Author-X-Name-First: Purushottam Author-X-Name-Last: Meena Author-Name: Rajendra Tibrewala Author-X-Name-First: Rajendra Author-X-Name-Last: Tibrewala Title: Buyback and risk-sharing contracts to mitigate the supply and demand disruption risks Abstract: Events like the recent COVID-19 create major disruptions in global supply chains. Companies find it difficult to manage business continuity under supply uncertainties and disruptions. This paper investigates the buyer's optimal ordering decisions under stochastic demand, supply uncertainty, and disruption risks. We consider a two-echelon supply chain consisting of a single buyer and two suppliers. The main supplier is cheaper, but exposed to the risks of random yield and disruption. The backup supplier is perfectly reliable, but relatively expensive. An analytical model is developed using contract-based mechanisms considering the risks of demand uncertainty, supply disruption, and random yield. Two typologies of contracts with suppliers are considered, namely, risks sharing contract and buyback contract. A numerical study is performed to explore the effects of different parameters on the supply chain members' profits, providing guidelines for managers regarding how the supply chain's risks and demand uncertainty influence the ordering decisions. [Received: 5 November 2019; Accepted: 22 August 2020] Journal: European J. of Industrial Engineering Pages: 550-581 Issue: 4 Volume: 15 Year: 2021 Keywords: supply disruption; COVID-19; random yield; demand uncertainty; buyback contract; ordering policy; risk-sharing contracts. File-URL: http://www.inderscience.com/link.php?id=116140 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:4:p:550-581 Template-Type: ReDIF-Article 1.0 Author-Name: Setareh Torabzadeh Author-X-Name-First: Setareh Author-X-Name-Last: Torabzadeh Author-Name: Ertunga C. Ozelkan Author-X-Name-First: Ertunga C. Author-X-Name-Last: Ozelkan Title: Fuzzy aggregate production planning with flexible requirement profile for plan stability in uncertain environments Abstract: In this paper, a production plan stability control technique called flexible requirement profile (FRP) is combined with fuzzy aggregate production planning (APP) to not only handle the planning system uncertainties, but also to maintain the stability of the production plans when re-planning. More specifically, this paper proposes two new fuzzy aggregate planning models namely the fuzzy Max-Min FRP-APP and fuzzy ranking FRP-APP. The proposed models are tested on five industry-based cases and the results are compared to the crisp FRP-APP, and traditional fuzzy APP models with no stability considerations. The results indicate that the proposed fuzzy FRP-APP model is able to yield comparable stability and cost performance as the crisp FRP-APP model but produce noticeably more stable production plans compared to the non-FRP-APP models without significantly sacrificing the cost. [Received: 30 June 2019; Accepted: 12 August 2020] Journal: European J. of Industrial Engineering Pages: 514-549 Issue: 4 Volume: 15 Year: 2021 Keywords: stability; aggregate production planning; APP; flexible requirements profile; FRP; fuzzy programming. File-URL: http://www.inderscience.com/link.php?id=116142 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:4:p:514-549 Template-Type: ReDIF-Article 1.0 Author-Name: Raid Al-Aomar Author-X-Name-First: Raid Author-X-Name-Last: Al-Aomar Author-Name: Abdallah Dweekat Author-X-Name-First: Abdallah Author-X-Name-Last: Dweekat Title: Simulation-based assessment of IoT-functionality in perishable dairy products Abstract: This paper presents a framework for simulation-based assessment of next-generation IoT-enabled supply chains with a focus on perishable dairy products. The framework integrates real-time data capturing with supply chain modelling and dynamic performance management. The concept of complex event processing (CEP) is utilised to implement IoT functionality. The aim is to reduce waste and losses caused by outdated items, shortages, and inventory discrepancies. The approach is illustrated through a simulation of dairy products perishability in a three-echelon supply chain. Simulation experiments were used to assess the impact of enabling two IoT functionalities; adjusting quantities distributed to retailers based on shelf-life and moving dairy products amongst retailers based on the proximity of their expiration. Simulation results have shown substantial improvement in both economic and operational KPIs of dairy products perishability. Results were also used to trade-off the percentage of expired milk and the inventory fill-rate. [Submitted: 6 August 2020; Accepted: 1 December 2020] Journal: European J. of Industrial Engineering Pages: 852-875 Issue: 6 Volume: 15 Year: 2021 Keywords: simulation modelling; supply chain performance management; internet-of-things; product perishability; dairy products. File-URL: http://www.inderscience.com/link.php?id=118493 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:6:p:852-875 Template-Type: ReDIF-Article 1.0 Author-Name: Ali Ekici Author-X-Name-First: Ali Author-X-Name-Last: Ekici Author-Name: Okan Örsan Özener Author-X-Name-First: Okan Örsan Author-X-Name-Last: Özener Author-Name: Milad Elyasi Author-X-Name-First: Milad Author-X-Name-Last: Elyasi Title: Supplier selection and order allocation in the presence of suppliers with exact annual capacity Abstract: In this paper, we focus on the supplier selection and order quantity allocation for a single retailer. The retailer orders a product from multiple suppliers with capacities, adds value to the product and fulfils the demand while meeting the minimum quality level. There is a distinct difference between our work and the prior works in the literature in that we assume the (annual) capacities of the suppliers to be exact annual capacities, i.e., the total order amount in a given calendar/fiscal year from a supplier must be less than or equal to its capacity. First, we discuss the implications of this exact annual capacity assumption on the ordering policy of the retailer. Next, to determine an ordering policy, we propose a heuristic algorithm using a novel idea of iteratively updating the annual ordering cost estimates. We demonstrate the efficacy of the proposed algorithm on randomly generated instances. [Submitted: 18 March 2019; Accepted: 22 November 2020] Journal: European J. of Industrial Engineering Pages: 803-824 Issue: 6 Volume: 15 Year: 2021 Keywords: supplier selection; long-run average annual capacity; perfect rate; capacitated suppliers; exact annual capacity. File-URL: http://www.inderscience.com/link.php?id=118496 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:6:p:803-824 Template-Type: ReDIF-Article 1.0 Author-Name: Papatya S. Bıçakcı Author-X-Name-First: Papatya S. Author-X-Name-Last: Bıçakcı Author-Name: Tusan Derya Author-X-Name-First: Tusan Author-X-Name-Last: Derya Author-Name: İmdat Kara Author-X-Name-First: İmdat Author-X-Name-Last: Kara Title: Solution approaches for the parallel machine order acceptance and scheduling problem with sequence-dependent setup times, release dates and deadlines Abstract: Order acceptance and scheduling problem arises when there is limited capacity to process all orders in a make-to-order environment. The paper examines the identical parallel machines order acceptance and scheduling problem with sequence-dependent setup times, release dates and deadlines. The extant literature is deeply researched, and it is concluded that well-designed mathematical formulations are still necessitated in this area. Therefore, a new formulation is proposed for this problem and a recent formulation is chosen from the literature in order to make the comparison. An extensive computational analysis is conducted to test the performance of the formulations. The proposed formulation outperformed the existing one in terms of run times and the number of optimal values. Besides, a variable neighbourhood search-based simulated annealing algorithm is propounded to solve large-sized instances. As a result, it is observed that the heuristic algorithm can solve large-sized instances effectively in a very short span of time. [Received: 18 December 2019; Accepted: 25 April 2020] Journal: European J. of Industrial Engineering Pages: 295-318 Issue: 3 Volume: 15 Year: 2021 Keywords: parallel machine; order acceptance and scheduling; release dates; sequence-dependent setup times; mathematical formulation; heuristic algorithm. File-URL: http://www.inderscience.com/link.php?id=115171 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:3:p:295-318 Template-Type: ReDIF-Article 1.0 Author-Name: Mohsen Lashgari Author-X-Name-First: Mohsen Author-X-Name-Last: Lashgari Author-Name: Reza Kia Author-X-Name-First: Reza Author-X-Name-Last: Kia Author-Name: Fariborz Jolai Author-X-Name-First: Fariborz Author-X-Name-Last: Jolai Title: Robust optimisation to design a dynamic cellular manufacturing system integrating group layout and workers' assignment Abstract: In this paper, a robust optimisation approach is proposed to solve a mathematical model integrating cell formation, group layout and operators assignment decisions under a dynamic situation. The main aim of applying a robust approach is to obtain an optimal design of a cellular manufacturing system that is robust with respect to encountered uncertainties in part demands and processing times. The integrated model incorporates several design attributes including operations sequence, group layout, equal-area facilities multi-rows layout, flexible cell reconfiguration, operators hiring/firing and training, operator available time, limitations of cell size and uncertain processing times and part demands. Two illustrative numerical examples are solved to investigate the validity of the robust model. Regarding the NP-hardness of the proposed model, an efficient simulated annealing algorithm is implemented. Some test problems either generated randomly or taken from the literature are solved and the results are compared with the ones obtained using CPLEX. [Received: 31 May 2019; Accepted: 3 May 2020] Journal: European J. of Industrial Engineering Pages: 319-351 Issue: 3 Volume: 15 Year: 2021 Keywords: dynamic cellular manufacturing system; robust optimisation; group layout; worker assignment; mixed-integer nonlinear program; simulated annealing. File-URL: http://www.inderscience.com/link.php?id=115172 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:3:p:319-351 Template-Type: ReDIF-Article 1.0 Author-Name: Pouyan Nikzad Author-X-Name-First: Pouyan Author-X-Name-Last: Nikzad Author-Name: Hokey Min Author-X-Name-First: Hokey Author-X-Name-Last: Min Author-Name: Farhad Yousofi Moghadam Author-X-Name-First: Farhad Yousofi Author-X-Name-Last: Moghadam Title: Redesigning multi-echelon integrated distribution networks using the Lagrangian relaxation heuristics Abstract: With constant changes in customer and supplier bases in the midst of rapid globalisation and rising e-commerce activities, supply chain professionals need to reassess the existing distribution network more frequently than ever before. Such reassessment may involve the complex array of the phase-out, relocation, consolidation, centralisation, and risk pooling of warehousing facilities across the entire supply chain. Since the supply chain includes an intertwined network of suppliers, customers and third-party intermediaries, the problem of redesigning the distribution network (DNRP) poses many challenges. To solve such a challenging problem, we develop and propose a nonlinear optimisation model. This model takes into account the multi-echelon links and dynamic interdependence among supply chain partners. The proposed model was structured within the dynamic knapsack framework where a known quantity of resources is available and demands for those resources arrive randomly over time. In this framework, we develop a new heuristic algorithm based on the Lagrangian relaxation, sub-gradient, and branch and bound methods for solving the DNRP. The practicality and computational efficiency of the proposed model and algorithm were verified through a series of model experiments under what-if problem scenarios. [Received: 9 May 2019; Accepted: 8 May 2020] Journal: European J. of Industrial Engineering Pages: 352-380 Issue: 3 Volume: 15 Year: 2021 Keywords: facility network redesign; dynamic knapsack problem; Lagrangian relaxation; risk pooling. File-URL: http://www.inderscience.com/link.php?id=115173 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:3:p:352-380 Template-Type: ReDIF-Article 1.0 Author-Name: Bin Chen Author-X-Name-First: Bin Author-X-Name-Last: Chen Author-Name: Wenying Xie Author-X-Name-First: Wenying Author-X-Name-Last: Xie Author-Name: Fuyou Huang Author-X-Name-First: Fuyou Author-X-Name-Last: Huang Author-Name: Juan He Author-X-Name-First: Juan Author-X-Name-Last: He Title: Collaboration and sharing in a retailer-led supply chain with yield uncertainty and loss aversion Abstract: This paper addresses a retailer-led supply chain in which a loss-averse supplier subject to yield uncertainty sells products to a risk-neutral retailer facing stochastic demand. An option contract is introduced to develop collaboration and sharing models to improve channel performance and achieve supply chain coordination. We derive the closed-form solution for the optimal production policy, and show that option contract is a viable alternative to effectively mitigate the serious conflicts between the dominant retailer and the supplier, which leads to a win-win situation. We analyse how the loss-averse behaviour of the supplier affects the production strategy and contract design. Also, we discuss how to share profit between the retailer and the supplier to achieve Pareto-improvement. In addition, we examine the role of option contract for achieving channel coordination and Pareto-improvement under loss aversion and single-side uncertainty. [Received: 5 November 2019; Accepted: 31 May 2020] Journal: European J. of Industrial Engineering Pages: 381-404 Issue: 3 Volume: 15 Year: 2021 Keywords: supply chain coordination; Pareto-improvement; option contract; yield uncertainty; loss aversion. File-URL: http://www.inderscience.com/link.php?id=115174 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:3:p:381-404 Template-Type: ReDIF-Article 1.0 Author-Name: Clarissa Fullin Barco Author-X-Name-First: Clarissa Fullin Author-X-Name-Last: Barco Author-Name: Moacir Godinho Filho Author-X-Name-First: Moacir Godinho Author-X-Name-Last: Filho Title: The effect of transfer lot size on manufacturing lead time: a stochastic analysis Abstract: This paper aims to explore, in a quantitative way, the effect of production and transfer lot size on the manufacturing lead time in an environment subject to uncertainties. In order to achieve this objective, a Monte Carlo simulation model is proposed, and several scenarios are analysed, considering six shop-floor variables. The results demonstrate that transfer lot size has little effect on lead time when operating with a manufacturing lot size away from optimal lot size. In order to obtain an excellent performance concerning lead time, it is first necessary to reduce the manufacturing lot size before making efforts to reduce transfer lot size. The results also show that adopting an optimal manufacturing lot size allows the production system to be more stable, allowing shorter lead times. The effect of a supplier manufacturing lot size smaller than optimal lot size on retailer safety stock is disastrous. This result is worse when the desired cycle service level and the demand coefficient of variability are high. [Submitted: 9 November 2019; Accepted: 28 November 2020] Journal: European J. of Industrial Engineering Pages: 825-851 Issue: 6 Volume: 15 Year: 2021 Keywords: manufacturing lead time; transfer lot; manufacturing lot; safety stocks; uncertainty; Monte Carlo simulation. File-URL: http://www.inderscience.com/link.php?id=118502 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:6:p:825-851 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: Wanying Wei Author-X-Name-First: Wanying Author-X-Name-Last: Wei Author-Name: Dong Xie Author-X-Name-First: Dong Author-X-Name-Last: Xie Author-Name: Siyu Wang Author-X-Name-First: Siyu Author-X-Name-Last: Wang Title: Logistics service supply chain coordination mechanism: a perspective of customer experience level Abstract: Continuously improving the customer experience level (CEL) becomes a consensus among companies and has a profound impact on the coordination of logistics service supply chain (LSSC), but it has been ignored by existing research. By establishing Stackelberg game models, we investigate the coordination mechanism of LSSC from the perspective of CEL, and obtain many unexpected findings. First, LSSC cannot be coordinated in a benchmark. Secondly, the role of buyback contract or quality supervision in coordinating the supply chain is limited. However, perfect coordination of LSSC can be achieved if quality supervision and buyback contracts are adopted simultaneously. Finally, when there is no condition to implement quality supervision, we propose an alternative mechanism. In summary, we prove the limitations of the buyback contract and quality supervision in the coordination supply chain through modelling, and creatively propose two feasible LSSC coordination mechanisms to make up for the existing research gaps. [Submitted: 29 August 2019; Accepted: 5 June 2020] Journal: European J. of Industrial Engineering Pages: 405-437 Issue: 3 Volume: 15 Year: 2021 Keywords: customer experience level; CEL; logistics service supply chain coordination; buyback contract; quality supervision; exchange leadership. File-URL: http://www.inderscience.com/link.php?id=115176 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:3:p:405-437 Template-Type: ReDIF-Article 1.0 Author-Name: Pablo Biswas Author-X-Name-First: Pablo Author-X-Name-Last: Biswas Author-Name: Bhaba R. Sarker Author-X-Name-First: Bhaba R. Author-X-Name-Last: Sarker Title: Optimal control of a multi-supplier and multi-buyer supply chain system with JIT delivery Abstract: A <i>just-in-time</i> centred production-facility supply chain consists of raw material suppliers, manufacturer, and retailers. This paper considers the concept where the production of finished goods follows continuous production cycles. In this scenario, it is assumed that the inventory build-up during production cycles of the concurrent cycle overlap the pure demand consumption cycle to reduce the idle time suggested by previous researchers. Considering this situation, a supply chain inventory models for raw materials, and finished goods supply are developed for multiple suppliers and multiple buyers. In addition, this paper considered that different suppliers deliver the raw materials in instantaneous replenishments supply, and the finished goods are delivered to multiple buyers in a fixed amount after a fixed interval of time (known as just-in-time delivery) according to buyers' demand. The problem in this research is formulated as an integer nonlinear programming problem and heuristic solutions are developed to solve it with the help of integer approximations and divide-and-conquer technique. The solution methodologies suggested lead to estimates of optimum production quantity and minimum total system cost. The solutions are verified through numerical examples and illustrated the effectiveness of the method with sensitivity analyses. [Submitted: 27 September 2019; Accepted: 3 January 2020] Journal: European J. of Industrial Engineering Pages: 745-776 Issue: 6 Volume: 15 Year: 2021 Keywords: supply chain system; just-in-time delivery; multi-buyer; multi-supplier and single manufacturer. File-URL: http://www.inderscience.com/link.php?id=118504 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:6:p:745-776 Template-Type: ReDIF-Article 1.0 Author-Name: Weihua Liu Author-X-Name-First: Weihua Author-X-Name-Last: Liu 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 Author-Name: Di Wang Author-X-Name-First: Di Author-X-Name-Last: Wang Title: The conflict handling mechanisms of intelligent logistics ecological chains: a perspective of trust behaviour under information asymmetry Abstract: The intelligent logistics ecological chain (ILEC) imposes strict requirements on the selection of logistics service providers (LSPs), while the trust behaviour and information asymmetry are two key factors need to be considered. We consider the vertical quality difference of LSP in ILEC and information asymmetry and build the Stacklberg games, to find the conditions for the occurrence of conflicts caused by quality fraud. Then we propose blockchain mechanism to resolve this conflict. We derive important conclusions and contributions. First, when logistics platform integrator (LPI) has low (high) trust in LSP, LSP always chooses to be honest (mimic). Second, there is a win-win situation between LPI and high-quality LSP, while a zero-sum game between LPI and low-quality LSP. Finally, when cooperating with low-quality LSP in low (high) trust levels, LPI can adopt blockchain technology (punishment mechanism). [Submitted: 27 June 2020; Accepted: 20 November 2020] Journal: European J. of Industrial Engineering Pages: 777-802 Issue: 6 Volume: 15 Year: 2021 Keywords: intelligent logistics ecological chain; ILEC; trust behaviour; blockchain; conflict handling mechanism. File-URL: http://www.inderscience.com/link.php?id=118517 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:eujine:v:15:y:2021:i:6:p:777-802