Article ID: | iaor20091341 |
Country: | United Kingdom |
Volume: | 7 |
Issue: | 1 |
Start Page Number: | 59 |
End Page Number: | 78 |
Publication Date: | Mar 2008 |
Journal: | Journal of Mathematical Modelling and Algorithms |
Authors: | Marinakis Yannis, Marinaki Magdalene |
Keywords: | location, vehicle routing & scheduling, heuristics: tabu search |
This paper introduces a new hybrid algorithmic nature inspired approach based on particle swarm optimization, for solving successfully one of the most popular logistics management problems, the location routing problem (LRP). The proposed algorithm for the solution of the location routing problem, the hybrid particle swarm optimization (HybPSO-LRP), combines a particle swarm optimization (PSO) algorithm, the multiple phase neighborhood search – greedy randomized adaptive search procedure (MPNS-GRASP) algorithm, the expanding neighborhood search (ENS) strategy and a path relinking (PR) strategy. The algorithm is tested on a set of benchmark instances. The results of the algorithm are very satisfactory for these instances and for six of them a new best solution has been found.