Work

A Simple and Efficient Artificial Bee Colony Algorithm

Year: 2013

Type: article

Abstract: Artificial bee colony (ABC) is a new population-based stochastic algorithm which has shown good search abilities on many optimization problems. However, the original ABC shows slow convergence speed during the search process. In order to enhance the performance of ABC, this paper proposes a new artificial bee colony (NABC) algorithm, which modifies the search pattern of both employed and onlooker bees. A solution pool is constructed by storing some best solutions of the current swarm. New candidate solutions are generated by searching the neighborhood of solutions randomly chosen from the solution pool. Experiments are conducted on a set of twelve benchmark functions. Simulation results show that our approach is significantly better or at least comparable to the original ABC and seven other stochastic algorithms.

Source: Mathematical Problems in Engineering

DOI: 10.1155/2013/526315

Authors: Yunfeng Xu, Ping Fan, Ling Yuan

Institutions: China People's Public Security University, Huazhong University of Science and Technology, Hubei University of Science and Technology

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,550

Funders: Ministry of Public Security of the People's Republic of China, Hubei University, Hubei University of Science and Technology