Multimodal Multi-objective Optimization Based on Parallel Zoning Search and Its Application

Abstract

Multimodal multi-objective optimization based on zoning search belongs to a decision space decomposition strategy,thus it has natural parallelism.To improve the solution efficiency,a parallel zoning search (PZS) using the parallel computing technique is proposed in this paper .In the PZS,the entire search space of multimodal multi-objective optimization problem is firs-tly divided into many subspaces,and then a selected multimodal multi-objective evolutionary algorithm is used to independently search each subregion via the parallel computing method.Finally,equivalent solutions are selected from solutions of all subspaces.To verify the effectiveness of the proposed method,two experiments are executed in the current study.The first experiment is that all compared algorithms use the same run time,the other is that all compared algorithms use the same number of function evaluation. The results show that the proposed method can effectively assist the selected multimodal multi-objective evolutionary algorithm in improving the quality of solutions in the decision space under the same calculation time,and can save the computational time under the same number of function evaluations.The multimodal multi-objective evolutionary algorithm combined with PZS is also used to solve the multimodal multi-objective problem of energy consumption of sea-rail intermodal transportation,in which carbon emission is considered.The obtained results can provide decision support for the environmental protection and transportation time issues in the sea-rail intermodal transportation.

Keywords

• multimodal multi-objective optimization|zoning search|high-performance computing|sea-rail intermodal transportation|green shipping