Fuzzy multi-objective optimization for wheat flour supply chain considering raw material substitution

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 min-imize 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.