Particle swarm optimization (PSO) is an evolutionary computation
technique; it has shown its effectiveness as an efficient, fast and simple
method of optimization. In this paper, the mathematical model represents
NP-hard in the strong sense; since any instance of the quadratic assignment
problem (QAP), I will implement the particle swarm optimization (PSO) for the
quadratic assignment problem (QAP). The results show that the PSO is an appropriate
optimization tool for use in determining the train location in the
transshipment yard by comparing it with previous studies to know the PSO’s
Cite this paper
Mohamed, A. and Peng, Q. (2014). Particle Swarm Optimization (PSO) Performance in Solving the Train Location Problem at Transshipment Yard. Open Access Library Journal, 1, e1024. doi: http://dx.doi.org/10.4236/oalib.1101024.
Liu, H. and Abraham, A. (2007) A Hybrid Fuzzy Variable Neighborhood Particle Swarm Optimization Algorithm for Solving Quadratic Assignment Problems. Journal of Universal Computer Science, 13, 1032-1054.