Improved binary artificial bee colony algorithm

The artificial bee colony (ABC) algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’ food search behavior. Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space, modification is r...

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Vydáno v:Frontiers of information technology & electronic engineering Ročník 22; číslo 8; s. 1080 - 1091
Hlavní autor: Durgut, Rafet
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hangzhou Zhejiang University Press 01.08.2021
Springer Nature B.V
Témata:
Algorithms
Communications Engineering
Computer Hardware
Computer Science
Computer Systems Organization and Communication Networks
Electrical Engineering
Electronics and Microelectronics
Evolutionary algorithms
Heuristic methods
Instrumentation
Libraries
Networks
Operations research
Optimization
Research Article
Search algorithms
Source code
Swarm intelligence
Artificial bee colony
Binary optimization
二进制优化
TP301.6
人工蜂群
Uncapacitated facility location problem (UFLP)
无容量限制的设施选址位置问题 (UFLP)
ISSN:2095-9184, 2095-9230
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Popis
Shrnutí:The artificial bee colony (ABC) algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’ food search behavior. Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space, modification is required to apply it to binary optimization problems. In this study, we modify the ABC algorithm to solve binary optimization problems and name it the improved binary ABC (IbinABC). The proposed method consists of an update mechanism based on fitness values and the selection of different decision variables. Therefore, we aim to prevent the ABC algorithm from getting stuck in a local minimum by increasing its exploration ability. We compare the IbinABC algorithm with three variants of the ABC and other meta-heuristic algorithms in the literature. For comparison, we use the well-known OR-Library dataset containing 15 problem instances prepared for the uncapacitated facility location problem. Computational results show that the proposed algorithm is superior to the others in terms of convergence speed and robustness. The source code of the algorithm is available at https://github.com/rafetdurgut/ibinABC .
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ISSN:2095-9184
2095-9230
DOI:10.1631/FITEE.2000239