Multi-Objective Fixed-Charged Transportation Optimization based on Fuzzy-WSGA
The fuzzy rules-based weighted sum Genetic Algorithm (Fuzzy-WSGA) is proposed in the paper to solve the multi-objective fixed-charged transportation optimization problem (mfcTP). We put forward the elite preserving strategy when the Pareto optimal solutions are built by the arenas principle, which used weighted sum based on the AP algorithm to evaluate the fitness function and preserve the elite. We construct the fuzzy rule base for traffic distribution, which can easily express explicit knowledge, and the limitation of greedy algorithm can be avoided. The experimental results show that Fuzzy-WSGA can find better Pareto front and Pareto optimal solutions in much less time. So it is more effective than st-GA and m-GA in finding Pareto optimal solutions.
mfctp genetic algorithm wsga weighted sum ap fuzzy rules pareto optimal solution
Cui Xiaoke Zhang Hongwei
School of Computer Science Chengdu University of Information Technology Chengdu, P.R.China
国际会议
成都
英文
562-566
2010-07-09（万方平台首次上网日期，不代表论文的发表时间）