TY - JOUR
ID - 676306
TI - A new multi-objective mathematical model for a Citrus supply chain network design: Metaheuristic algorithms
JO - Journal of Optimization in Industrial Engineering
JA - JOIE
LA - en
SN - 2251-9904
AU - Fakhrzad, M.B.
AU - Goodarzian, F.
AD - Department of Industrial Engineering,Yazd University
AD - Yazd University
Y1 - 2021
PY - 2021
VL - 14
IS - 2
SP - 111
EP - 128
KW - citrus supply chain
KW - MINLP model
KW - Simulated Annealing Algorithm
KW - ant colony optimization algorithm
DO - 10.22094/joie.2020.570636.1571
N2 - Nowadays, the citrus supply chain has been motivated by both industrial practitioners and researchers due to several real-world applications. This study considers a four-echelon citrus supply chain, consisting of gardeners, distribution centers, citrus storage, and fruit market. A Mixed Integer Non-Linear Programming (MINLP) model is formulated, which seeks to minimize the total cost and maximize the profit of the Citrus supply chain network. Due to the complexity of the model when considering large-scale samples, two well-known meta-heuristic algorithms such as Ant Colony Optimization (ACO) and Simulated Annealing (SA) algorithms have been utilized. Additionally, a new multi-objective ACO algorithm based on a set of non-dominated solutions form the Pareto frontier developed to solve the mathematical model. An extensive comparison based on different measurements analyzed to find a performance solution for the developed problem in the three sizes (small, medium, and large-scale). Finally, the various outcomes of numerical experiments indicate that the MOACO algorithm is more reliable than other algorithms.
UR - http://www.qjie.ir/article_676306.html
L1 - http://www.qjie.ir/article_676306_f7d0f5c93b150d844515dad12cd55ea8.pdf
ER -