Comparing Three Proposed Meta-heuristics to Solve a New p-hub Locationallocation Problem

This paper presents a sophisticated mathematical model, in which the location of hubs is fixed and their capacity is determined based on facilities and factories allocated to it. Inorder to feed the client's nodes, different types of vehicles of different capacities are considered, in which the clients are allocated to hubs, and types and numbers of vehicles areallocated to the factory's facilities. To come up with solutions, we propose to use three metaheuristicalgorithms, namely, genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA). The efficiency and computational results of these algorithms are compared with one another.

Keywords:

Hub Location-allocation , Vehicle Capacity , Plant Production Capacity , Simulated Annealing , Genetic Algorithm , Particle Swarm Optimization