DISCRETE PARTICLE SWARM OPTIMIZATION FOR THE ORIENTEERING PROBLEM

Authors

  • Shanthi Muthuswamy Northern Illinois University
  • Sarah Lam Binghamton University

DOI:

https://doi.org/10.23055/ijietap.2011.18.2.384

Keywords:

Discrete particle swarm optimization, reduced variable neighborhood search, orienteering problem.

Abstract

Discrete particle swarm optimization (DPSO) is gaining popularity in the area of combinatorial optimization in the recent past due to its simplicity in coding and consistency in performance.  A DPSO algorithm has been developed for orienteering problem (OP) which has been shown to have many practical applications.  It uses reduced variable neighborhood search as a local search tool.  The DPSO algorithm was compared with ten heuristic models from the literature using benchmark problems.  The results show that the DPSO algorithm is a robust algorithm that can optimally solve the well known OP test problems.

Author Biographies

Shanthi Muthuswamy, Northern Illinois University

Assistant Professor

Department of Technology

Northern Illinois University

Sarah Lam, Binghamton University

Associate Professor

Systems Science and Industrial Engineering Department,

Binghamton University

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Published

2011-02-06

How to Cite

Muthuswamy, S., & Lam, S. (2011). DISCRETE PARTICLE SWARM OPTIMIZATION FOR THE ORIENTEERING PROBLEM. International Journal of Industrial Engineering: Theory, Applications and Practice, 18(2). https://doi.org/10.23055/ijietap.2011.18.2.384

Issue

Section

Operations Research