A particle swarm optimization algorithm for the continuous absolute p-center location problem with Euclidean distance

Abstract

The p-center location problem is concerned with determining the location of p centers in a plane/space to serve n demand points having fixed locations. The continuous absolute p-center location problem attempts to locate facilities anywhere in a space/plane with Euclidean distance. The continuous Euclidean p-center location problem seeks to locate p facilities so that the maximum Euclidean distance to a set of n demand points is minimized. A particle swarm optimization (PSO) algorithm previously advised for the solution of the absolute p-center problem on a network has been extended to solve the absolute p-center problem on space/plan with Euclidean distance. In this paper we develop a PSO algorithm for the continuous absolute p-center location problem to minimize the maximum Euclidean distance from each customer to his/her nearest facility, called “PSO-ED”. This problem is proven to be NP-hard. We tested the proposed algorithm “PSO-ED” on a set of 2D and 3D problems and compared the results with a branch and bound algorithm. The numerical experiments show that PSO-ED algorithm can solve optimally location problems with Euclidean distance including up to 1,904,711 points.

Authors and Affiliations

Hassan Rabie, Dr. Ihab El-Khodary, Prof. Assem Tharwat

Keywords

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  • EP ID EP88258
  • DOI 10.14569/IJACSA.2013.041215
  • Views 116
  • Downloads 0

How To Cite

Hassan Rabie, Dr. Ihab El-Khodary, Prof. Assem Tharwat (2013). A particle swarm optimization algorithm for the continuous absolute p-center location problem with Euclidean distance. International Journal of Advanced Computer Science & Applications, 4(12), 101-106. https://europub.co.uk/articles/-A-88258