Fuzzy Multi-Objective Optimization for Wheat Flour Supply Chain Considering Raw Material Substitution
Published 2020-09-30
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Keywords
- Fuzzy multi-objective optimization,
- Possibilistic programming,
- Fuzzy numbers,
- Raw material substitution,
- NSGA II
How to Cite
Copyright (c) 2023 International Journal of Industrial Engineering and Management
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)