Hybrid ITÖ Algorithm for Large-Scale Colored Traveling Salesman Problem

In the fields of intelligent transportation and multi-task cooperation, many practical problems can be modeled by colored traveling salesman problem (CTSP). When solving large-scale CTSP with a scale of more than 1000 dimensions, their convergence speed and the quality of their solutions are limited. This paper proposes a new hybrid ITÖ (HITÖ) algorithm, which integrates two new strategies, crossover operator and mutation strategy, into the standard ITÖ. In the iteration process of HITÖ, the feasible solution of CTSP is represented by the double chromosome coding, and the random drift and wave operators are used to explore and develop new unknown regions. In this process, the drift operator is executed by the improved crossover operator, and the wave operator is performed by the optimized mutation strategy. Experiments show that HITÖ is superior to the known comparison algorithms in terms of the quality solution.

Authors

Publication Details

Journal
Chinese Journal of Electronics
Published
2024-11-01
DOI
https://doi.org/10.23919/cje.2023.00.040
Citations
2
Primary Topic
Scheduling and Timetabling Solutions
Type
article
Field-Weighted Citation Impact
0.98

Funders

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article

Hybrid ITÖ Algorithm for Large-Scale Colored Traveling Salesman Problem

Xueshi Dong
2 citations
Chinese Journal of Electronics
Scheduling and Timetabling Solutions
0.98
article

Hybrid ITÖ Algorithm for Large-Scale Colored Traveling Salesman Problem

Xueshi Dong
article en
2 citations

Abstract

In the fields of intelligent transportation and multi-task cooperation, many practical problems can be modeled by colored traveling salesman problem (CTSP). When solving large-scale CTSP with a scale of more than 1000 dimensions, their convergence speed and the quality of their solutions are limited. This paper proposes a new hybrid ITÖ (HITÖ) algorithm, which integrates two new strategies, crossover operator and mutation strategy, into the standard ITÖ. In the iteration process of HITÖ, the feasible solution of CTSP is represented by the double chromosome coding, and the random drift and wave operators are used to explore and develop new unknown regions. In this process, the drift operator is executed by the improved crossover operator, and the wave operator is performed by the optimized mutation strategy. Experiments show that HITÖ is superior to the known comparison algorithms in terms of the quality solution.

Chinese Journal of ElectronicsVol. 33(6)
Natural Science Foundation of Shandong Province
Openalex Percentile: Top 20%
Scheduling and Timetabling Solutions
0.98
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