Solving TSP by using combinatorial Bees algorithm with nearest neighbor method

Bees Algorithm (BA) is a popular meta-heuristic method that has been used in many different optimization areas for years. In this study, a new version of combinatorial BA is proposed and explained in detail to solve Traveling Salesman Problems (TSPs). The nearest neighbor method was used in the popu...

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Bibliographic Details
Published in:Neural computing & applications 2023, Vol.35 (2), p.1863-1879
Main Author: Sahin, Murat
Format: Article
Language:English
Subjects:
Artificial Intelligence
Cities
Combinatorial analysis
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Experimentation
Genetic algorithms
Heuristic
Heuristic methods
Image Processing and Computer Vision
Methods
Neighborhoods
Optimization
Original Article
Probability and Statistics in Computer Science
Search algorithms
Traveling salesman problem
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Summary:Bees Algorithm (BA) is a popular meta-heuristic method that has been used in many different optimization areas for years. In this study, a new version of combinatorial BA is proposed and explained in detail to solve Traveling Salesman Problems (TSPs). The nearest neighbor method was used in the population generation section of BA, and the Multi-Insert function was added to the local search section instead of the Swap function. To see the efficiency of the proposed method, 24 different TSPs were used in experimentation and the obtained results were compared with both classical combinatorial BA and other successful meta-heuristic methods. After detailed analyses and experimental studies on different problems, it has been observed that the proposed method performs well for TSPs and competes well with other methods.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-022-07816-y