Two Metaheuristic Approaches for p-Hub Center Location Problem under Capacity Constraints

Abstract

Hub location problem is one of the new issues in location problems. This kind of location problem is widely used in transportation systems. In this paper, we investigate p-hub center location allocation problem under capacity constraint. The aim of the proposed model is to determine the location of hub nodes and the allocation of non-hub nodes to the hub in such a way that the maximum traveling time is minimized. In addition, since the problem is an NP hard problem, two metaheuristic algorithms including simulated annealing algorithm and ant colony are developed for solving large size real world problems. The performances of the proposed algorithms are examined via some numerical examples taken from known related benchmark sets (AP dataset). The best solutions found using metaheuristic algorithms are also compare to the results achieved using Lingo software. The results demonstrate that the proposed algorithms are able to find optimum or near optimum solutions in acceptable run times.

Keywords

• Simulated annealing
• Ant colony optimization
• Capacity constraint
• p-hub center location