Improved Cuckoo Search Algorithm Applied to Multi-objective Optimization of Crowd Evacuation

Authors

Chongjie Dong, 1.Dongguan Polytechnic, DongGuan 523808, China;;
Liu Yi, 2.Hunan Agricultural Machinery Management Bureau, Changsha 410011, China;
Peng Yong, 1.Dongguan Polytechnic, DongGuan 523808, China;;

Abstract

Abstract: The crowd evacuation problem is a multi-objective optimization problem in large public places under the emergency, but because of the conflict between multiple objectives in multi-objective optimization problem, it is difficult to make the multiple targets achieve the optimal at the same time. The most popular solution is an evolution multi objective optimization algorithm for the characteristics of heuristic search of population and the partial order relation. Cuckoo search algorithm is a new search algorithm which was found in the behavior of cuckoo nest spawning lies, the basic cuckoo search algorithm is lack of vitality, and search is slow. From the change of cuckoo search algorithm search diversity to improve the ability to solve the cuckoo algorithm in optimization problems, a new algorithm was applied to multi-objective optimization of crowd evacuation, which has achieved good results.

Recommended Citation

Dong, Chongjie; Yi, Liu; and Yong, Peng (2020) "Improved Cuckoo Search Algorithm Applied to Multi-objective Optimization of Crowd Evacuation," Journal of System Simulation: Vol. 28: Iss. 5, Article 9.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss5/9

First Page

1063

Revised Date

2015-07-03

DOI Link

https://doi.org/

Last Page

1069

CLC

TP391.9

Recommended Citation

Dong Chongjie, Liu Yi, Peng Yong. Improved Cuckoo Search Algorithm Applied to Multi-objective Optimization of Crowd Evacuation[J]. Journal of System Simulation, 2016, 28(5): 1063-1069.