Open AccessAn empirical study on solving an integrated production and distribution problem with a hybrid strategy
Author(s) -
Feng Li,
Li Zhou,
Guangshu Xu,
Hongguang Lu,
Kai Wang,
SangBing Tsai
Publication year - 2018
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0206806
Subject(s) - supply chain , computer science , simulated annealing , sorting , mathematical optimization , scheduling (production processes) , genetic algorithm , fuzzy logic , algorithm , mathematics , artificial intelligence , political science , law
Coordination is essential for improving supply chain performance, and one of the most critical factors in achieving the coordination of a supply chain is the integrated research of production and distribution. In this paper, a novel two-stage hybrid solution methodology is proposed. In the first stage, products are processed on the serial machines of multiple manufacturers located in two industrial parks. A fuzzy multi-objective scheduling optimization is performed using a modified non-dominated sorting genetic algorithm II (NSGA-II). The result obtained in the first stage is used in the second stage to optimize the distribution scheduling problem using a modified genetic annealing algorithm (GAA). Finally, simulation results verify both the feasibility and efficiency of the proposed solution methodology.