Accelerating Artificial Bee Colony algorithm with adaptive local search

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• 作者：Shimpi Singh Jadon ; Jagdish Chand Bansal ; Ritu Tiwari ; Harish Sharma
• 关键词：Artificial Bee Colony ; Memetic algorithm ; Optimization ; Exploration鈥揺xploitation ; Swarm Intelligence
• 刊名：Memetic Computing
• 出版年：2015
• 出版时间：September 2015
• 年：2015
• 卷：7
• 期：3
• 页码：215-230
• 全文大小：666 KB
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• 作者单位：Shimpi Singh Jadon (1)
  Jagdish Chand Bansal (2)
  Ritu Tiwari (1)
  Harish Sharma (3)
  
  1. ABV-Indian Institute of Information Technology and Management, Gwalior, India
  2. South Asian University, New Delhi, India
  3. Vardhaman Mahaveer Open University, Kota, India
  
• 刊物类别：Engineering
• 刊物主题：Applied Mathematics and Computational Methods of Engineering
  Artificial Intelligence and Robotics
  Automation and Robotics
  Complexity
  Bioinformatics
  Applications of Mathematics
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1865-9292

文摘

Artificial Bee Colony (ABC) algorithm has been emerged as one of the latest Swarm Intelligence based algorithm. Though, ABC is a competitive algorithm as compared to many other optimization techniques, the drawbacks like preference on exploration at the cost of exploitation and skipping the true solution due to large step sizes, are also associated with it. In this paper, two modifications are proposed in the basic version of ABC to deal with these drawbacks: solution update strategy is modified by incorporating the role of fitness of the solutions and a local search based on greedy logarithmic decreasing step size is applied. The modified ABC is named as accelerating ABC with an adaptive local search (AABCLS). The former change is incorporated to guide to not so good solutions about the directions for position update, while the latter modification concentrates only on exploitation of the available information of the search space. To validate the performance of the proposed algorithm AABCLS, \(30\) benchmark optimization problems of different complexities are considered and results comparison section shows the clear superiority of the proposed modification over the Basic ABC and the other recent variants namely, Best-So-Far ABC (BSFABC), Gbest guided ABC (GABC), Opposition based levy flight ABC (OBLFABC) and Modified ABC (MABC).