# VCMTSP

**Repository Path**: absinthhh/vcmtsp

## Basic Information

- **Project Name**: VCMTSP
- **Description**: This directory contains the source code of VCMTSP
- **Primary Language**: Python
- **License**: MulanPSL-1.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2024-04-17
- **Last Updated**: 2024-07-29

## Categories & Tags

**Categories**: Uncategorized

**Tags**: VCMTSP

## README

# VCMTSP

This directory contains the main code of the proposed benchmark in the following paper:

Xin-Ai Dou, Qiang Yang*, Xu-Dong Gao, Zhen-Yu Lu, and Dan-Ting Duan, "Benchmark for Multiple Traveling Salesman Problem with Visiting Constraints", in International Conference on Machine Intelligence Theory and Applications, 2024.


Before running the code, the following notice should be paid attention to:

1.An example of generating vcmtsp instances based on "VCMTSP.py" is given in "generate_vcmtsp.py".

2.The parameters used to generate the vcmtsp instances are set in the generator method in "VCMTSP.py".

3.The parameter "depot" in VCMTSP can be set to None, 0, 1-n or "center". When "depot" is set to None or 0, the resulting instance is a multi-depot VCMTSP instance. When "depot" is set as 1-n, the resulting instance is a single-depot VCMTSP instance with a specified depot. When "depot" is set as "center", the city at the center is assigned as the depot.

4.The parameter "feature" in VCMTSP can be set to "tight", "moderate", or "loose". The parameter "feature" is set to "moderate" by default.

5.The parameter "No" in VCMTSP is an identifier, in order to distinguish between different VCMTSP instances with the same settings.

6.The parameter "m" in VCMTSP can only be set to an integer greater than 3.


This code is only for academic use and if you use this code, please kindly cite the following related papers:

[1] Xin-Ai Dou, Qiang Yang*, Xu-Dong Gao, Zhen-Yu Lu, and Dan-Ting Duan, "Benchmark for Multiple Traveling Salesman Problem with Visiting Constraints", in International Conference on Machine Intelligence Theory and Applications, 2024.

[2] Cong Bao, Qiang Yang*, Xu-Dong Gao, Zhen-Yu Lu, and Jun Zhang, "Ant Colony Optimization with Shortest Distance Biased Dispatch for Visiting Constrained Multiple Traveling Salesmen Problem," in Proc. Genet. Evol. Comput. Conf. Companion, pp. 77-80, 2022.

[3] Cong Bao, Qiang Yang*, Xu-Dong Gao, and Jun Zhang, "A Comparative Study on Population-Based Evolutionary Algorithms for Multiple Traveling Salesmen Problem with Visiting Constraints," in IEEE Symp. Ser. Comput. Intell., pp. 01-08, 2021.

[4] Cong Bao, Qiang Yang*, Xu-Dong Gao, and Zhen-Yu Lu, "Genetic Algorithm with Adapted Crossover Operators for Multiple Traveling Salesmen Problem with Visiting Constraints," in IEEE Int. Conf. Syst. Man Cybern., pp. 3033-3039, 2022.

[4] Xin-Ai Dou, Qiang Yang*, Pei-Lan Xu, Xu-Dong Gao, and Zhen-Yu Lu, "Comparative Study on Different Encoding Strategies for Multiple Traveling Salesmen Problem," in IEEE Int. Conf. Syst. Man Cybern., pp. 1437-1442, 2023.

[5] Nuo Xu, Deming Wu, Qiang Yang* et al., "Ant Colony Optimization for Multiple Travelling Salesmen Problem with Pivot Cities," in Int. Conf. Adv. Comput. Intell., pp. 1-8, 2023.

[6] Bing Sun, Chuan Wang*, Qiang Yang* et al., "Ant Colony Optimization for Balanced Multiple Traveling Salesmen Problem," in Int. Conf. Comput. Sci. Comput. Intell., pp. 476-481, 2021.

[7] Xin-Xin Liu, Dong Liu, Qiang Yang* et al., "Comparative Analysis of Five Local Search Operators on Visiting Constrained Multiple Traveling Salesmen Problem," in IEEE Symp. Ser. Comput. Intell., pp. 01-08, 2021.


if you have any question, please contact absinthdou@gmail.com or absinthhh@163.com.

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