International Journal of Industrial Engineering and Management

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Vol. 11 No. 3 (2020)
Original Research Article

Fuzzy Multi-Objective Optimization for Wheat Flour Supply Chain Considering Raw Material Substitution

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  • Trisna Trisna,
  • Marimin Marimin,
  • Yandra Arkeman,
  • Titi Candra Sunarti
Trisna Trisna
Department of Industrial Engineering, Faculty of Engineering, Universitas Malikussaleh, Jl. Batam Kampus Bukit Indah Lhokseumawe
Bio
Marimin Marimin
Department of Agroindustrial Technology, Faculty of Agricultural Technology, Bogor Agricultural University, Campus IPB Darmaga
Bio
Yandra Arkeman
Department of Agroindustrial Technology, Faculty of Agricultural Technology, Bogor Agricultural University, Campus IPB Darmaga
Bio
Titi Candra Sunarti
Department of Agroindustrial Technology, Faculty of Agricultural Technology, Bogor Agricultural University, Campus IPB Darmaga
Bio
DOI: https://doi.org/10.24867/IJIEM-2020-3-263

Published 2020-09-30

abstract views: 64 // FULL TEXT ARTICLE (PDF): 0


Keywords

  • Fuzzy multi-objective optimization,
  • Possibilistic programming,
  • Fuzzy numbers,
  • Raw material substitution,
  • NSGA II

How to Cite

Trisna, T., Marimin, M., Arkeman, Y., & Sunarti, T. C. (2020). Fuzzy Multi-Objective Optimization for Wheat Flour Supply Chain Considering Raw Material Substitution. International Journal of Industrial Engineering and Management, 11(3), 180–191. https://doi.org/10.24867/IJIEM-2020-3-263

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

This study aimed to develop a multi-objective optimization model of the wheat flour supply chain considering raw material substitution in which supplier capacity and product demand were considered in uncertain conditions. There are four objectives to be achieved: to minimize the total cost and to maximize product quality, reliability, and local flour usage. We established multi-objective fuzzy mixed integer non-linear programming to solve the problem and used non-dominated sorting genetic algorithm (NSGA) II methods to found the best solution. The result provides a referral for a decision maker to design the optimal substituted wheat flour supply chain.

 

Article history: Received (July 30, 2020); Revised (September 12, 2020); Accepted (September 14, 2020); Published online (September 29, 2020)  

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