Closed-loop logistics (forward and reverse logistics) has received increased attention of late due to customer expectations, greater environmental concerns, and economic aspects. Unlike previous works, which consider single products or single periods in multi-objective function problems, this paper considers a multi-product multi-period closed-loop logistics network with regard to facility expansion as a facility location-allocation problem, which is closer to real-world scenarios. A multi-objective mixed integer nonlinear programming formulation is developed to minimize the total cost, the product delivery time, and the used product collection time. The model is linearized by defining new variables and adding new constraints to the model. Then, to solve the model, a priority-based genetic algorithm is proposed that uses straight encoding and decoding methods. To assess the performance of the above algorithm, its final solutions and CPU times are compared to those generated by an initial priority-based genetic algorithm from the recent literature and the lower bound obtained by CPLEX. The numerical results show that the straight priority-based genetic algorithm outperforms the initial priority-based genetic algorithm at least in terms of obtaining a reasonable quality of final solutions for closed-loop logistics problems.
Accepté le :
DOI : 10.1051/ro/2014032
Mots-clés : Closed-loop logistics, multi-objective decision making, genetic algorithm, forward and reverse logistics
@article{RO_2015__49_2_243_0,
author = {Mehrbod, Mehrdad and Xue, Zhaojie and Miao, Lixin and Lin, Wei-Hua},
editor = {Blazewicz, Jacek and Pesch, Erwin and Philipps, Cynthia and Trystram, Denis and Zhang, Guochuan},
title = {A {Straight} {Priority-Based} {Genetic} {Algorithm} for a {Logistics} {Network}},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {243--264},
publisher = {EDP-Sciences},
volume = {49},
number = {2},
year = {2015},
doi = {10.1051/ro/2014032},
zbl = {1310.90015},
language = {en},
url = {http://archive.numdam.org/articles/10.1051/ro/2014032/}
}
TY - JOUR AU - Mehrbod, Mehrdad AU - Xue, Zhaojie AU - Miao, Lixin AU - Lin, Wei-Hua ED - Blazewicz, Jacek ED - Pesch, Erwin ED - Philipps, Cynthia ED - Trystram, Denis ED - Zhang, Guochuan TI - A Straight Priority-Based Genetic Algorithm for a Logistics Network JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2015 SP - 243 EP - 264 VL - 49 IS - 2 PB - EDP-Sciences UR - http://archive.numdam.org/articles/10.1051/ro/2014032/ DO - 10.1051/ro/2014032 LA - en ID - RO_2015__49_2_243_0 ER -
%0 Journal Article %A Mehrbod, Mehrdad %A Xue, Zhaojie %A Miao, Lixin %A Lin, Wei-Hua %E Blazewicz, Jacek %E Pesch, Erwin %E Philipps, Cynthia %E Trystram, Denis %E Zhang, Guochuan %T A Straight Priority-Based Genetic Algorithm for a Logistics Network %J RAIRO - Operations Research - Recherche Opérationnelle %D 2015 %P 243-264 %V 49 %N 2 %I EDP-Sciences %U http://archive.numdam.org/articles/10.1051/ro/2014032/ %R 10.1051/ro/2014032 %G en %F RO_2015__49_2_243_0
Mehrbod, Mehrdad; Xue, Zhaojie; Miao, Lixin; Lin, Wei-Hua. A Straight Priority-Based Genetic Algorithm for a Logistics Network. RAIRO - Operations Research - Recherche Opérationnelle, New challenges in scheduling theory, Tome 49 (2015) no. 2, pp. 243-264. doi : 10.1051/ro/2014032. http://archive.numdam.org/articles/10.1051/ro/2014032/
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