Fuzzy discrete particle swarm optimization for solving traveling salesman problem

Wei Pang; Kangping Wang; Chunguang Zhou; Longjiang Dong

doi:10.1109/CIT.2004.1357292

Fuzzy discrete particle swarm optimization for solving traveling salesman problem

Wei Pang, Kangping Wang, Chunguang Zhou, Longjiang Dong

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Particle swarm optimization, as an evolutionary computing technique, has succeeded in many continuous problems, but research on discrete problems especially combinatorial optimization problem has been done little according to Kennedy and Eberhart (1997) and Mohan and Al-kazemi (2001). In this paper, a modified particle swarm optimization (PSO) algorithm was proposed to solve a typical combinatorial optimization problem: traveling salesman problem (TSP), which is a well-known NP-hard problem. Fuzzy matrices were used to represent the position and velocity of the particles in PSO and the operators in the original PSO formulas were redefined. Then the algorithm was tested with concrete examples in TSPLIB, experiment shows that the algorithm can achieve good results.

Original language	English
Title of host publication	Fourth International Conference on Computer and Information Technology, 2004
Publisher	IEEE
Number of pages	5
ISBN (Print)	0769522165
DOIs	https://doi.org/10.1109/CIT.2004.1357292
Publication status	Published - 30 Nov 2004

Keywords

fuzzy set theory
NP-hard problem
particle swarm optimization
random number generation
testing
traveling salesman problem
evolutionary computation
cities and towns
educational institutions
matrix algebra

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10.1109/CIT.2004.1357292

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title = "Fuzzy discrete particle swarm optimization for solving traveling salesman problem",

abstract = "Particle swarm optimization, as an evolutionary computing technique, has succeeded in many continuous problems, but research on discrete problems especially combinatorial optimization problem has been done little according to Kennedy and Eberhart (1997) and Mohan and Al-kazemi (2001). In this paper, a modified particle swarm optimization (PSO) algorithm was proposed to solve a typical combinatorial optimization problem: traveling salesman problem (TSP), which is a well-known NP-hard problem. Fuzzy matrices were used to represent the position and velocity of the particles in PSO and the operators in the original PSO formulas were redefined. Then the algorithm was tested with concrete examples in TSPLIB, experiment shows that the algorithm can achieve good results.",

keywords = "fuzzy set theory, NP-hard problem, particle swarm optimization, random number generation, testing, traveling salesman problem, evolutionary computation, cities and towns, educational institutions, matrix algebra",

author = "Wei Pang and Kangping Wang and Chunguang Zhou and Longjiang Dong",

year = "2004",

month = nov,

day = "30",

doi = "10.1109/CIT.2004.1357292",

language = "English",

isbn = "0769522165",

booktitle = "Fourth International Conference on Computer and Information Technology, 2004",

publisher = "IEEE",

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TY - GEN

T1 - Fuzzy discrete particle swarm optimization for solving traveling salesman problem

AU - Pang, Wei

AU - Wang, Kangping

AU - Zhou, Chunguang

AU - Dong, Longjiang

PY - 2004/11/30

Y1 - 2004/11/30

N2 - Particle swarm optimization, as an evolutionary computing technique, has succeeded in many continuous problems, but research on discrete problems especially combinatorial optimization problem has been done little according to Kennedy and Eberhart (1997) and Mohan and Al-kazemi (2001). In this paper, a modified particle swarm optimization (PSO) algorithm was proposed to solve a typical combinatorial optimization problem: traveling salesman problem (TSP), which is a well-known NP-hard problem. Fuzzy matrices were used to represent the position and velocity of the particles in PSO and the operators in the original PSO formulas were redefined. Then the algorithm was tested with concrete examples in TSPLIB, experiment shows that the algorithm can achieve good results.

AB - Particle swarm optimization, as an evolutionary computing technique, has succeeded in many continuous problems, but research on discrete problems especially combinatorial optimization problem has been done little according to Kennedy and Eberhart (1997) and Mohan and Al-kazemi (2001). In this paper, a modified particle swarm optimization (PSO) algorithm was proposed to solve a typical combinatorial optimization problem: traveling salesman problem (TSP), which is a well-known NP-hard problem. Fuzzy matrices were used to represent the position and velocity of the particles in PSO and the operators in the original PSO formulas were redefined. Then the algorithm was tested with concrete examples in TSPLIB, experiment shows that the algorithm can achieve good results.

KW - fuzzy set theory

KW - NP-hard problem

KW - particle swarm optimization

KW - random number generation

KW - testing

KW - traveling salesman problem

KW - evolutionary computation

KW - cities and towns

KW - educational institutions

KW - matrix algebra

U2 - 10.1109/CIT.2004.1357292

DO - 10.1109/CIT.2004.1357292

M3 - Conference contribution

SN - 0769522165

BT - Fourth International Conference on Computer and Information Technology, 2004

PB - IEEE

ER -

Fuzzy discrete particle swarm optimization for solving traveling salesman problem

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Keywords

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