JOURNAL ARTICLE

An improved hybrid algorithm for traveling salesman problem

Abstract

An improved artificial bee colony (ABC&VNS) to settle the traveling salesman problem (TSP) is described in this paper. This hybrid algorithm's principal character is to incorporate the solution construction mechanism of the artificial bee colony (ABC) with variable neighborhood search (VNS) to exploit the intrinsic structure of the solutions to acquire the high quality solution. Besides, three novel neighborhood structures are present, in which problem-specific knowledge is utilized respectively, to improve both the search efficiency and quality of VNS. Finally, the experiments for benchmark TSP instances are carried out to verify that the proposed algorithm is capable of maintaining high performance to solve the TSP, which is compared with the best existing approaches in the way of solution quality.

Keywords:
Travelling salesman problem Benchmark (surveying) Artificial bee colony algorithm Computer science Mathematical optimization Variable neighborhood search 2-opt Exploit Algorithm Local search (optimization) Hybrid algorithm (constraint satisfaction) Quality (philosophy) Variable (mathematics) Artificial intelligence Metaheuristic Mathematics

Metrics

2
Cited By
0.00
FWCI (Field Weighted Citation Impact)
12
Refs
0.09
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Vehicle Routing Optimization Methods
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Advanced Algorithms and Applications
Physical Sciences →  Engineering →  Control and Systems Engineering

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