JOURNAL ARTICLE

Comparison Study of Multiple Traveling Salesmen Problem using Genetic Algorithm

Shalini Singh

Year: 2013 Journal:   IOSR Journal of Computer Engineering Vol: 13 (3)Pages: 17-22   Publisher: International Organization Of Scientific Research (IOSR)

Abstract

Multiple traveling salesman problems (MTSP) are a typical computationally complex combinatorial optimization problem, which is an extension of the famous traveling salesman problem (TSP).The MTSP can be generalized to a wide variety of routing and scheduling problems.The paper makes the attempt to show how Genetic Algorithm (GA) can be applied to the MTSP with ability constraint.In this paper, we compare MTSP in term of distance and iteration by considering several set of cities.The computational results show that the proposed algorithm can find competitive solutions within rational time, especially for large scale problems.

Keywords:
Computer science Genetic algorithm Algorithm Machine learning

Metrics

10
Cited By
0.00
FWCI (Field Weighted Citation Impact)
4
Refs
0.15
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence

Related Documents

BOOK-CHAPTER

Solving the Multiobjective Multiple Traveling Salesmen Problem Using Membrane Algorithm

Juanjuan He

Communications in computer and information science Year: 2014 Pages: 171-175
BOOK-CHAPTER

A Novel Approach to Solve Multiple Traveling Salesmen Problem by Genetic Algorithm

András KirályJános Abonyi

Studies in computational intelligence Year: 2010 Pages: 141-151
JOURNAL ARTICLE

An Improved Partheno-Genetic Algorithm for Open Path Multi-Depot Multiple Traveling Salesmen Problem

Ping LouKun XuJunwei YanZheng Xiao

Journal:   Journal of Physics Conference Series Year: 2021 Vol: 1848 (1)Pages: 012002-012002
© 2026 ScienceGate Book Chapters — All rights reserved.