A bi-objective model for a multi-echelon supply chain design considering efficiency and customer satisfaction: a case study in plastic parts industry

  • Seyed Babak Ebrahimi


One of the fundamental challenges of today’s manufacturing systems is the contradiction between cost efficiency and customer satisfaction. Finding a good balance between good customer satisfaction and supply chain efficiency is a critical problem in the supply chain management. To achieve this goal, a bi-objective mathematical model is suggested in this paper to maximize the efficiency of network and also customer satisfaction. This multi-period and multi-product supply chain network design model consists of suppliers, factories, distribution centers (DCs), and customers. The proposed bi-objective mixed-integer non-linear programming (MINLP) model is a member of the NP-hard class of optimization problems. Hence, two well-known multi-objective metaheuristic algorithms namely, Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Non-dominated Ranked Genetic Algorithm (NRGA) are employed to solve the proposed model. The author uses Taguchi method for tuning the parameters of algorithms in order to achieve better performances. Moreover, a case study in the plastic industry is performed to collect data from the north region of Iran. Some well-known multi-objective metrics such as analysis of variance (ANOVA) is used to measure the performance of the proposed framework. Finally, results demonstrate the efficiency of the proposed framework.


Supply chain network design Customer satisfaction Multi-objective metaheuristic algorithm Plastic industry Taguchi method 


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© Springer-Verlag London Ltd., part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Industrial EngineeringK. N. Toosi University of TechnologyTehranIran

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