Paper Info
Title
A multi-objective hybrid genetic algorithm to minimize the total cost and delivery tardiness in a reverse logistics.
Abstract
In the recent environmental protection the reverse logistics of the used product is one of the most important research topics. The reverse logistics is the process flow of used-products that are collected to be reproduced so that they can be sold again to customers after some processing. We propose a multi-objective hybrid genetic algorithm (mo-hGA) combined with Fuzzy Logic Controller (FLC) for efficiently dealing with multi-objective reverse logistics network (mo-RLN) problem. The aim of this paper is firstly to formulate mo-RLN model, and secondly to optimize it by mo-hGA method proposed with reusable system configuration. In particular two objective functions to be minimized total costs of mo-RLN, (i.e. fixed opening cost, transportation cost and inventory cost) and also minimized delivery tardiness in all periods are considered in the model. We will clear each objective function (i.e. total costs and total delivery tardiness), computational time and number of Pareto solutions with LINGO, pri-awGA (priority-based GA with adaptive weight approach) and mo-hGA proposed with numerical examples. For demonstrating the effectiveness of the proposed model, we evaluate with the numerical examples and simulate it with a bottles distilling/sale company as a case study in Busan, Korea.
Year
DOI
Venue
2015
10.1007/s11042-013-1594-6
Multimedia Tools and Applications
Keywords
Field
DocType
Multi-objective reverse logistics network (mo-RLN), Pri-awGA (priority-based GA with adaptive weight approach), Multi-objective hybrid genetic algorithm (mo-hGA), Fuzzy logic controller (FLC)
Transportation cost,Computer science,Reverse logistics,System configuration,Artificial intelligence,Genetic algorithm,Mathematical optimization,Tardiness,Pattern recognition,Simulation,Inventory cost,Total cost,Pareto principle
Journal
Volume
Issue
ISSN
74
20
1573-7721
Citations 
PageRank 
References 
9
0.64
19
Authors
4
Name
Order
Citations
PageRank
Jeong-eun Lee1533.17
Kyung-Yong Chung2115480.87
Kang-Dae Lee3151.44
Mitsuo Gen41873130.43