A New Approach to Solving the Fixed Destination Multi-Depot Multiple Traveling Salesman Problem using Genetic Algorithms

Kamran Kardel; Nikbakhsh Javadian; Freydoun Adbesh

doi:10.13140/RG.2.1.3958.2244

A New Approach to Solving the Fixed Destination Multi-Depot Multiple Traveling Salesman Problem using Genetic Algorithms

Kamran Kardel, Nikbakhsh Javadian, Freydoun Adbesh

Manufacturing Engineering

Mazandaran University of Science and Technology

Research output: Contribution to conference › Presentation

Abstract

The fixed destination multi depot multiple traveling salesmen problem (MmTSP) in which more than one salesmen depart from several starting cities and having returned to the starting city, form tours so that each city is visited with exactly one salesman and the tour lengths stay within certain limits. This problem is of a great complexity and few investigations have been done on it before. In this paper we propose a new GA chromosome and related operators for the MmTSP and compare the theoretical properties and computational performance of the some common operators and strategies of genetic algorithms. We also compare results in problems with small dimensions to the optimal answers obtained by solving the problems by Lingo 8.

Original language	American English
DOIs	https://doi.org/10.13140/RG.2.1.3958.2244
State	Published - Dec 10 2007
Event	International Conference on Optimization: Techniques and Applications (ICOTA) - Shanghai, China Duration: Dec 1 2010 → …

Conference

Conference	International Conference on Optimization: Techniques and Applications (ICOTA)
Period	12/1/10 → …

Disciplines

Manufacturing

Keywords

Fixed destination
Genetic algorithms
Multi-depot
Multiple traveling salesman problem
New approach
Solving

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Cite this

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title = "A New Approach to Solving the Fixed Destination Multi-Depot Multiple Traveling Salesman Problem using Genetic Algorithms",

abstract = " The fixed destination multi depot multiple traveling salesmen problem (MmTSP) in which more than one salesmen depart from several starting cities and having returned to the starting city, form tours so that each city is visited with exactly one salesman and the tour lengths stay within certain limits. This problem is of a great complexity and few investigations have been done on it before. In this paper we propose a new GA chromosome and related operators for the MmTSP and compare the theoretical properties and computational performance of the some common operators and strategies of genetic algorithms. We also compare results in problems with small dimensions to the optimal answers obtained by solving the problems by Lingo 8.",

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AU - Javadian, Nikbakhsh

AU - Adbesh, Freydoun

PY - 2007/12/10

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N2 - The fixed destination multi depot multiple traveling salesmen problem (MmTSP) in which more than one salesmen depart from several starting cities and having returned to the starting city, form tours so that each city is visited with exactly one salesman and the tour lengths stay within certain limits. This problem is of a great complexity and few investigations have been done on it before. In this paper we propose a new GA chromosome and related operators for the MmTSP and compare the theoretical properties and computational performance of the some common operators and strategies of genetic algorithms. We also compare results in problems with small dimensions to the optimal answers obtained by solving the problems by Lingo 8.

AB - The fixed destination multi depot multiple traveling salesmen problem (MmTSP) in which more than one salesmen depart from several starting cities and having returned to the starting city, form tours so that each city is visited with exactly one salesman and the tour lengths stay within certain limits. This problem is of a great complexity and few investigations have been done on it before. In this paper we propose a new GA chromosome and related operators for the MmTSP and compare the theoretical properties and computational performance of the some common operators and strategies of genetic algorithms. We also compare results in problems with small dimensions to the optimal answers obtained by solving the problems by Lingo 8.

KW - Fixed destination

KW - Genetic algorithms

KW - Multi-depot

KW - Multiple traveling salesman problem

KW - New approach

KW - Solving

UR - https://doi.org/10.13140/RG.2.1.3958.2244

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DO - 10.13140/RG.2.1.3958.2244

M3 - Presentation

T2 - International Conference on Optimization: Techniques and Applications (ICOTA)

Y2 - 1 December 2010

ER -

A New Approach to Solving the Fixed Destination Multi-Depot Multiple Traveling Salesman Problem using Genetic Algorithms

Abstract

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Keywords

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