Research on multi-objective location-routing problem of reverse logistics based on GRA with entropy weight

There are many objectives in location-routing problem of reverse logistics, which are helpful to improve practicability of reverse logistics. In this paper, a multi-objective programming model about location-routing of reverse logistics is proposed, and grey relational analysis and particle swarm optimization are combined to resolve it. The results of example show that the model and multi-objective algorithm are effective for dealing with multi-objective location-routing problem of reverse logistics.

[1]  Zhang Qi-shan Research of reverse logistics location and routing problem based on improved particle swarm optimization algorithm , 2010 .

[2]  Massimiliano Caramia,et al.  A heuristic approach to long-haul freight transportation with multiple objective functions , 2009 .

[3]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[4]  Liu Hong,et al.  Location of logistics distribution center with grey demand and grey production capacity based on hybrid PSO , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[5]  Hong Liu,et al.  Location of Logistics Distribution Centers with Grey Production Capacity Based on Hybrid PSO , 2010 .

[6]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[7]  Gerald W. Evans,et al.  A bi-objective reverse logistics network analysis for post-sale service , 2008, Comput. Oper. Res..

[8]  Nilay Shah,et al.  Logistical network design with robustness and complexity considerations , 2007 .

[9]  Chung-Ho Wang,et al.  Optimization of an established multi-objective delivering problem by an improved hybrid algorithm , 2009, 2009 International Conference on Computers & Industrial Engineering.

[10]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[11]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[12]  Russell C. Eberhart,et al.  Particle swarm with extended memory for multiobjective optimization , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[13]  Mir Saman Pishvaee,et al.  A memetic algorithm for bi-objective integrated forward/reverse logistics network design , 2010, Comput. Oper. Res..

[14]  Hong Liu,et al.  Research on location-routing problem of reverse logistics with grey recycling demands based on PSO , 2011, Grey Syst. Theory Appl..

[15]  Henry C. W. Lau,et al.  A fuzzy guided multi-objective evolutionary algorithm model for solving transportation problem , 2009, Expert Syst. Appl..

[16]  Jeffrey Forrest,et al.  Novel models of grey relational analysis based on visual angle of similarity and nearness , 2011, Grey Syst. Theory Appl..

[17]  Carlos A. Coello Coello,et al.  Handling multiple objectives with particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[18]  Zhang Qi Chaos-Particle Swarm Optimization Algorithm and Its Application to Mechanical Optimal Design , 2007 .

[19]  Hong Liu,et al.  The Vehicle Routing Problem of Reverse logistics with grey recycling demand based on hybrid PSO , 2010, 2010 IEEE 17Th International Conference on Industrial Engineering and Engineering Management.

[20]  M. N. Vrahatis,et al.  Particle swarm optimization method in multiobjective problems , 2002, SAC '02.

[21]  C. K. Y. Lin,et al.  Multi-objective metaheuristics for a location-routing problem with multiple use of vehicles on real data and simulated data , 2006, Eur. J. Oper. Res..

[22]  Sifeng Liu,et al.  Grey Control Systems , 2010 .

[23]  Sai Ho Chung,et al.  A study of distribution center location based on the rough sets and interactive multi-objective fuzzy decision theory , 2011 .