A Multi-Species Artificial Bee Colony Algorithm and Its Application for Crowd Simulation

作     者：Wang, Shouna Liu, Hong Gao, Kaizhou Zhang, Jianxin 

作者机构：Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Shandong Peoples R China Shandong Prov Key Lab Distributed Comp Software N Jinan 250014 Shandong Peoples R China Macau Univ Sci & Technol Inst Syst Engn Macau 999078 Peoples R China 

出 版 物：《IEEE ACCESS》 (IEEE Access)

年 卷 期：2019年第7卷

页      面：2549-2558页

核心收录：

基　　金：National Natural Science Foundation of China [61876102  61472232  61272094] 

主　　题：Artificial bee colony algorithm dynamic strategy of segmentation co-evolution strategy function optimization problems crowd simulation for evacuation 

摘      要：The artificial bee colony (ABC) algorithm has the problem of slow convergence and may be trapped into local optimum. In this paper, a multi-species ABC (MABC) algorithm is proposed based on the multi-swarm model. The MABC algorithm uses dynamic segmentation of the swarm and a co-evolution strategy. The strategy of dynamic segmentation divides the colony into multiple sub-species, and the species communicate with each other using the co-evolution strategy. The combined global communication pattern and local communication pattern are applied among sub-species. In order to test the performance of the algorithm, experiments are conducted on the CEC 05 Test Functions. To test the performance of the algorithm in crowd simulation for evacuation, we simulate it through a crowd simulation system for evacuation, and the MABC algorithm improves the efficiency of crowd evacuation.