Abstract | ||
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The bee colony optimization (BCO) algorithm with a linear dance function (denoted as the BCO-Linear algorithm) is inspired by the bees' foraging behaviors, in which waggle dances are modeled as a communication medium among bees. Through these informative waggle dances, more bees are recruited toward exploring more profitable search regions. In the BCO-Linear algorithm, a fitter bee is allowed to dance longer, and the dance duration is determined by a linear function with a scaling parameter that requires manual tuning. This article presents a dynamic fuzzy-based dance mechanism, ie, the BCO-Fuzzy algorithm, to solve the manual tuning problem. A fuzzy-based approach is applied to regulate the duration of waggle dances instead of regulating the dance duration using a linear function. The proposed BCO-Fuzzy algorithm comprises parameters that are dynamically controlled based on the feedback of the search process, therefore overcoming the limitation of manual parameter tuning of the BCO-Linear algorithm. The BCO-Fuzzy algorithm is evaluated comprehensively using a set of benchmark traveling salesman problems. The experimental results show that the performance of the BCO-Fuzzy algorithm is comparable with that of the BCO-Linear algorithm. Specifically, the dynamic fuzzy-based dance mechanism improves the BCO algorithm in terms of rewarding dance instances near the inflection point. Performance comparison with other nature-inspired algorithms proves the effectiveness of the proposed BCO-Fuzzy algorithm. |
Year | DOI | Venue |
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2018 | 10.1111/coin.12159 | COMPUTATIONAL INTELLIGENCE |
Keywords | Field | DocType |
bee colony optimization,dynamic parameter control,fuzzy logic,traveling salesman problem,waggle dance | Dance,Computer science,Waggle dance,Fuzzy logic,Travelling salesman problem,Artificial intelligence,Optimization algorithm,Machine learning | Journal |
Volume | Issue | ISSN |
34.0 | 4.0 | 0824-7935 |
Citations | PageRank | References |
1 | 0.35 | 27 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
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Shin Siang Choong | 1 | 14 | 2.20 |
Li-Pei Wong | 2 | 109 | 8.32 |
Chee Peng Lim | 3 | 1459 | 122.04 |