论文信息 - A hybrid differential evolution and estimation of distribution algorithm for the multi-point dynamic aggregation problem

A hybrid differential evolution and estimation of distribution algorithm for the multi-point dynamic aggregation problem

The multi-point dynamic aggregation (MPDA) is a typical task planning problem. In order to solve the MPDA problem efficiently a hybrid differential evolution (DE) and estimation of distribution algorithm (EDA) called DE-EDA is proposed in this paper, which combines the merits of DE and EDA. The DE-EDA has been applied to multiple MPDA instances of different scales, and compared with EDA and two versions of DE in convergence speed and solution quality separately. The results demonstrate the DE-EDA can solve the MPDA problem effectively.

Jia Zhang | Chen Chen | Rong Hao | Bin Xin | Lihua Dou

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