Notice of RetractionMulti-objective fixed-charged transportation optimization based on Fuzzy-WSGA

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

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 arena´s 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.