Particle Swarm Optimization and Grey Wolf Optimizer to Solve Continuous p-Median Location Problems

• Published in: Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges Vol. 77; pp. 415 - 435
• Main Author: Rabie, Hassan Mohamed
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2020; Springer International Publishing
• Series: Studies in Big Data
• Subjects: Grey wolf; Location problem; median; NFL theorem; Particle swarm
• ISBN: 3030593371; 9783030593377
• ISSN: 2197-6503; 2197-6511
• DOI: 10.1007/978-3-030-59338-4_21

The continuous p-median location problem is to locate p facilities in the Euclidean plane in such a way that the sum of distances between each demand point and its nearest median/facility is minimized. In this chapter, the continuous p-median problem is studied, and a proposed Grey Wolf Optimizer (GWO) algorithm, which has not previously been applied to solve this problem, is presented and compared to a proposed Particle Swarm Optimization (PSO) algorithm. As an experimental evidence for the NFL theorem, the experimental results showed that the no algorithm can outperformed the other in all cases, however the proposed PSO has better performance in most of the cases. The experimental results show that the two proposed algorithms have better performance than other PSO methods in the literature.