Experimental evaluation of meta-heuristics for multi-objective capacitated multiple allocation hub location problem

Multi-objective capacitated multiple allocation hub location problem (MOCMAHLP) is a variation of classic problem, which deals with network design, considering both the number and hubs connections between spokes, as well routing flow on network. In this study, we offer two meta-heuristic approaches based non-dominated sorting genetic algorithm (NSGA-II) archived multi-objective simulated annealing method (AMOSA) to solve MOCMAHLP. We attuned AMOSA approach obtain feasible solutions for developed five different neighborhood operators in approach. Moreover, NSGA-II approach, novel problem-specific mutation operators. To statistically analyze behavior algorithms, conducted experiments well-known data sets, namely Turkish Australian Post (AP). Hypervolume indicator used performance metric measure effectiveness given sets. experimental thorough tests are fine-tune proposed types AMOSA. Fine-tuning reveal that NSGA-II, probability does not have real effect set, whereas lower probabilities slightly better AP set. among operators, one adds/removes specific links according temperature (NS-5) performs than others After analyzing comparison our performed best settings. As result, conclude algorithms able find problem. larger, smaller size networks.