论文信息 - An Improved Immune-Based Multi-modal Function Optimization Algorithm

An Improved Immune-Based Multi-modal Function Optimization Algorithm

The aim of this paper is to design an adaptive artificial immune algorithm for solving multi-modal optimization problems effectively and speedily. Based on analyzing the characteristics and disadvantages of CLONALG, an improved immune-based algorithm is proposed, which combines memory cells producing, network suppression and valley searching method. Testing benchmark functions show that it can fast find out all optimal solutions and local optimal solutions as many as possible without any prior knowledge.

Xu Zhang | Li Xu

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