A particle swarm optimization approach to the orienteering problem

Herby Dallarad, Sarah S.Y. Lam, Sadan Kulturel-Konak

Research output: Contribution to conferencePaper

3 Scopus citations

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 languageEnglish (US)
Publication statusPublished - Dec 1 2006
Event2006 IIE Annual Conference and Exposition - Orlando, FL, United States
Duration: May 20 2006May 24 2006

Other

Other2006 IIE Annual Conference and Exposition
CountryUnited States
CityOrlando, FL
Period5/20/065/24/06

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All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

Cite this

Dallarad, H., Lam, S. S. Y., & Kulturel-Konak, S. (2006). A particle swarm optimization approach to the orienteering problem. Paper presented at 2006 IIE Annual Conference and Exposition, Orlando, FL, United States.