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

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Abstract

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.

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Authors and Affiliations

  1. Department of Industrial Engineering, K. N. Toosi University of Technology, Pardis St. Molasadra Ave., Vanak Sq, Tehran, 19395-1999, Iran

    Seyed Babak Ebrahimi

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  1. Seyed Babak Ebrahimi
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Correspondence to Seyed Babak Ebrahimi.

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Ebrahimi, S.B. A bi-objective model for a multi-echelon supply chain design considering efficiency and customer satisfaction: a case study in plastic parts industry. Int J Adv Manuf Technol 95, 3631–3649 (2018). https://doi.org/10.1007/s00170-017-1437-0

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  • DOI: https://doi.org/10.1007/s00170-017-1437-0

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