### Abstract

Particle Swarm Optimization (PSO), developed by Kennedy and Eberhart in 1995, was inspired by social behavior of birds flocking or fish schooling. It is a population-based algorithm, where a swarm of particles fly in a multi-dimensional space, guided by their social dynamics while optimizing an objective function. The Orienteering Problem (OP), a variation of the traveling salesman problem, is a NP-hard benchmark problem. Given a set of nodes with associated scores, the objective of the OP is to find a path that maximizes the total score subject to a given time or distance constraint. This paper addresses the design of a PSO algorithm to solve one of the problem instances of the OP and discusses the preliminary results.

Original language | English (US) |
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Title of host publication | 2006 IIE Annual Conference and Exposition |

State | Published - 2006 |

Event | 2006 IIE Annual Conference and Exposition - Orlando, FL, United States Duration: May 20 2006 → May 24 2006 |

### Other

Other | 2006 IIE Annual Conference and Exposition |
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Country | United States |

City | Orlando, FL |

Period | 5/20/06 → 5/24/06 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Industrial and Manufacturing Engineering

### Cite this

*2006 IIE Annual Conference and Exposition*

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*2006 IIE Annual Conference and Exposition.*2006 IIE Annual Conference and Exposition, Orlando, FL, United States, 5/20/06.

**A particle swarm optimization approach to the orienteering problem.** / Dallarad, Herby; Lam, Sarah S Y; Kulturel-Konak, Sadan.

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

TY - GEN

T1 - A particle swarm optimization approach to the orienteering problem

AU - Dallarad, Herby

AU - Lam, Sarah S Y

AU - Kulturel-Konak, Sadan

PY - 2006

Y1 - 2006

N2 - Particle Swarm Optimization (PSO), developed by Kennedy and Eberhart in 1995, was inspired by social behavior of birds flocking or fish schooling. It is a population-based algorithm, where a swarm of particles fly in a multi-dimensional space, guided by their social dynamics while optimizing an objective function. The Orienteering Problem (OP), a variation of the traveling salesman problem, is a NP-hard benchmark problem. Given a set of nodes with associated scores, the objective of the OP is to find a path that maximizes the total score subject to a given time or distance constraint. This paper addresses the design of a PSO algorithm to solve one of the problem instances of the OP and discusses the preliminary results.

AB - Particle Swarm Optimization (PSO), developed by Kennedy and Eberhart in 1995, was inspired by social behavior of birds flocking or fish schooling. It is a population-based algorithm, where a swarm of particles fly in a multi-dimensional space, guided by their social dynamics while optimizing an objective function. The Orienteering Problem (OP), a variation of the traveling salesman problem, is a NP-hard benchmark problem. Given a set of nodes with associated scores, the objective of the OP is to find a path that maximizes the total score subject to a given time or distance constraint. This paper addresses the design of a PSO algorithm to solve one of the problem instances of the OP and discusses the preliminary results.

UR - http://www.scopus.com/inward/record.url?scp=84858464523&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84858464523&partnerID=8YFLogxK

M3 - Conference contribution

BT - 2006 IIE Annual Conference and Exposition

ER -