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
Link To Document :
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