Balanced Bee Colony Algorithm Based on Fitness Euclidean-distance Ratio

Authors

Zhang Ming, 1. School of Internet of Things, Jiangnan University, Wuxi 214122, China;;
Tian Na, 2. School of Humanities, Jiangnan University, Wuxi 214122, China;
Zhicheng Ji, 1. School of Internet of Things, Jiangnan University, Wuxi 214122, China;;

Abstract

Abstract: According to the power exploration and poor exploitation ability of artificial bee colony (ABC), a balanced bee colony (FER-ABC) was proposed. This algorithm modified the search equation based on “fitness Euclidean-distance ratio” and differential algorithm (DE). The FER strategy is useful for multi-optimization and the DE is beneficial to single- optimization. In order to exploit the advantages to full, a new search structure was proposed which balanced the exploitation and exploration. For continuous problems, the simulations on twelve benchmark functions indicate that this FER-ABC algorithm can improve the accuracy effectively and increase the convergence rate apparently. For the discrete problem, this proposed algorithm is proved to be feasible and advantageous on the simulation of four standard flexible job shop scheduling module.

Recommended Citation

Ming, Zhang; Na, Tian; and Ji, Zhicheng (2020) "Balanced Bee Colony Algorithm Based on Fitness Euclidean-distance Ratio," Journal of System Simulation: Vol. 27: Iss. 5, Article 9.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss5/9

First Page

980

Revised Date

2015-01-08

DOI Link

https://doi.org/

Last Page

989

CLC

TP301.6

Recommended Citation

Zhang Ming, Tian Na, Ji Zhicheng. Balanced Bee Colony Algorithm Based on Fitness Euclidean-distance Ratio[J]. Journal of System Simulation, 2015, 27(5): 980-989.