A particle swarm optimization approach to the orienteering problem

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

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations


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)
StatePublished - 2006
Event2006 IIE Annual Conference and Exposition - Orlando, FL, United States
Duration: May 20 2006May 24 2006


Other2006 IIE Annual Conference and Exposition
Country/TerritoryUnited States
CityOrlando, FL

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering


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