An efficient genetic algorithm for the traveling salesman problem with precedence constraints

Chiung Moon, Jongsoo Kim, Gyunghyun Choi, Yoon Ho Seo

Research output: Contribution to journalArticle

129 Citations (Scopus)

Abstract

The traveling salesman problem with precedence constraints (TSPPC) is one of the most difficult combinatorial optimization problems. In this paper, an efficient genetic algorithm (GA) to solve the TSPPC is presented. The key concept of the proposed GA is a topological sort (TS), which is defined as an ordering of vertices in a directed graph. Also, a new crossover operation is developed for the proposed GA. The results of numerical experiments show that the proposed GA produces an optimal solution and shows superior performance compared to the traditional algorithms.

Original languageEnglish
Pages (from-to)606-617
Number of pages12
JournalEuropean Journal of Operational Research
Volume140
Issue number3
DOIs
Publication statusPublished - 2002 Aug 1
Externally publishedYes

Fingerprint

salesman
Precedence Constraints
Traveling salesman problem
Travelling salesman problems
Efficient Algorithms
Genetic algorithms
Genetic Algorithm
Directed graphs
Combinatorial optimization
Combinatorial Optimization Problem
Directed Graph
Sort
Crossover
Optimal Solution
Numerical Experiment
Genetic algorithm
experiment
Experiments
performance

Keywords

  • Genetic algorithm
  • Optimization
  • Topological sort
  • Traveling salesman problem with precedence constraints

ASJC Scopus subject areas

  • Information Systems and Management
  • Management Science and Operations Research
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Modelling and Simulation
  • Transportation

Cite this

An efficient genetic algorithm for the traveling salesman problem with precedence constraints. / Moon, Chiung; Kim, Jongsoo; Choi, Gyunghyun; Seo, Yoon Ho.

In: European Journal of Operational Research, Vol. 140, No. 3, 01.08.2002, p. 606-617.

Research output: Contribution to journalArticle

@article{e84786c32dbe48898673d5aa5143c3fc,
title = "An efficient genetic algorithm for the traveling salesman problem with precedence constraints",
abstract = "The traveling salesman problem with precedence constraints (TSPPC) is one of the most difficult combinatorial optimization problems. In this paper, an efficient genetic algorithm (GA) to solve the TSPPC is presented. The key concept of the proposed GA is a topological sort (TS), which is defined as an ordering of vertices in a directed graph. Also, a new crossover operation is developed for the proposed GA. The results of numerical experiments show that the proposed GA produces an optimal solution and shows superior performance compared to the traditional algorithms.",
keywords = "Genetic algorithm, Optimization, Topological sort, Traveling salesman problem with precedence constraints",
author = "Chiung Moon and Jongsoo Kim and Gyunghyun Choi and Seo, {Yoon Ho}",
year = "2002",
month = "8",
day = "1",
doi = "10.1016/S0377-2217(01)00227-2",
language = "English",
volume = "140",
pages = "606--617",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier",
number = "3",

}

TY - JOUR

T1 - An efficient genetic algorithm for the traveling salesman problem with precedence constraints

AU - Moon, Chiung

AU - Kim, Jongsoo

AU - Choi, Gyunghyun

AU - Seo, Yoon Ho

PY - 2002/8/1

Y1 - 2002/8/1

N2 - The traveling salesman problem with precedence constraints (TSPPC) is one of the most difficult combinatorial optimization problems. In this paper, an efficient genetic algorithm (GA) to solve the TSPPC is presented. The key concept of the proposed GA is a topological sort (TS), which is defined as an ordering of vertices in a directed graph. Also, a new crossover operation is developed for the proposed GA. The results of numerical experiments show that the proposed GA produces an optimal solution and shows superior performance compared to the traditional algorithms.

AB - The traveling salesman problem with precedence constraints (TSPPC) is one of the most difficult combinatorial optimization problems. In this paper, an efficient genetic algorithm (GA) to solve the TSPPC is presented. The key concept of the proposed GA is a topological sort (TS), which is defined as an ordering of vertices in a directed graph. Also, a new crossover operation is developed for the proposed GA. The results of numerical experiments show that the proposed GA produces an optimal solution and shows superior performance compared to the traditional algorithms.

KW - Genetic algorithm

KW - Optimization

KW - Topological sort

KW - Traveling salesman problem with precedence constraints

UR - http://www.scopus.com/inward/record.url?scp=0036680981&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036680981&partnerID=8YFLogxK

U2 - 10.1016/S0377-2217(01)00227-2

DO - 10.1016/S0377-2217(01)00227-2

M3 - Article

VL - 140

SP - 606

EP - 617

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 3

ER -