DocumentCode
2404879
Title
Multi-Objective Fixed-Charged Transportation Optimization in Supply Chain Management
Author
Hongwei, Zhang ; Xiaoke, Cui ; Shurong, Zou
Author_Institution
Sch. of Comput. Sci., Chengdu Univ. of Inf. Technol., Chengdu, China
fYear
2010
fDate
7-9 May 2010
Firstpage
3247
Lastpage
3250
Abstract
For coping with the multi-objective fixed-charged transportation optimization problem (mfcTP) in SCM a new fuzzy rules-based particle swarm optimization algorithm called Fuzzy-PSO is proposed in the paper. In terms of this new algorithm base on the fitness vector function, we firstly construct the fuzzy rule base which is convenient to express the explicit knowledge, and then apply the fuzzy rulers to control the process of traffic distribution with the fixed-charged. The experimental results show that it can find better Pareto front and Pareto optimal solutions in the real-world problems even if nonlinear and discontinuous. So it is more effective than st-GA and m-GA.
Keywords
Pareto optimisation; fuzzy set theory; genetic algorithms; particle swarm optimisation; supply chain management; transportation; Pareto optimal solution; fitness vector function; fuzzy rules based particle swarm optimization algorithm; multiobjective fixed charged transportation optimization; process control; supply chain management; traffic distribution; Availability; Monitoring; Optimization; Particle swarm optimization; Presses; Production facilities; Transportation; PSO; Pareto front; Pruefer number; fitness vector function; fuzzy rules; mfcTP;
fLanguage
English
Publisher
ieee
Conference_Titel
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-0-7695-3997-3
Type
conf
DOI
10.1109/ICEE.2010.817
Filename
5591100
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