Multi-objective fixed-charged transportation optimization based on Fuzzy-EA

For coping with the multi-objective fixed-charged transportation optimization problem (mfcTP) a new fuzzy rules-based evolutionary algorithm called Fuzzy-EA 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 Fuzzy-EA 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 in finding Pareto optimal solutions.