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Critical-edge based tabu search algorithm for solving large-scale multi-vehicle Chinese postman problem
Jizhou Tang1,2, Lili He1,2, Yinghui Cao1,2
1School of Computer Science and Technology, Jilin University, Qianjin Street, Changchun, 130022, China.
Scientific Reports
|May 30, 2024
Summary
This study introduces CTA-kroutes, a novel algorithm for the challenging min-max multi-vehicle Chinese postman problem. It efficiently balances path lengths in large road networks, improving planning for tasks like urban inspection.
Area of Science:
- Operations Research
- Graph Theory
- Algorithm Design
Background:
- The min-max multi-vehicle Chinese postman problem (MM-MVCPP) is NP-hard, crucial for road network path planning.
- Large-scale networks present challenges in solution time and path length balancing.
Purpose of the Study:
- To develop an efficient algorithm for solving the MM-MVCPP in large-scale road networks.
- To improve the equalization of path lengths among multiple vehicles.
Main Methods:
- Proposed a critical-edge tabu search algorithm (CTA-kroutes).
- Initial solution generation via Eulerian path segmentation for balanced lengths.
- Iterative optimization using tabu search and critical edge movements.
- Solution refinement through de-duplication and optimal reconstruction.
Main Results:
- CTA-kroutes effectively balances multi-vehicle path lengths.
- Demonstrated applicability and efficiency on large-scale road networks.
- Improved solution quality compared to existing methods (implied).
Conclusions:
- CTA-kroutes provides an effective approach for the MM-MVCPP in large networks.
- The algorithm enhances path equalization, crucial for practical applications.
- Offers a viable solution for complex road network planning challenges.
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