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

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 ma...

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Bibliographic Details
Published in:IJIEM. International Journal of Industrial Engineering and Management (Online) Vol. 11; no. 3; pp. 180 - 191
Main Authors: Trisna, Trisna, Marimin, Marimin, Arkeman, Yandra, Candra Sunarti, Titi
Format: Journal Article
Language:English
Published: Novi Sad University of Novi Sad 01.09.2020
University of Novi Sad, Faculty of Technical Sciences
Subjects:
Decision making
Flour
fuzzy multi-objective optimization
fuzzy numbers
Genetic algorithms
Linear programming
Materials substitution
Mixed integer
Multiple objective analysis
Nonlinear programming
nsga ii
Optimization
possibilistic programming
raw material substitution
Sorting algorithms
Supply chains
Wheat
ISSN:2217-2661, 2683-345X
Online Access:Get full text
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Summary: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.
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ISSN:2217-2661
2683-345X
DOI:10.24867/IJIEM-2020-3-263