Optimizing the reliable hub location problem under separate backup hubs: a cuckoo algorithm

Hub location models have a significant impact in optimizing many logistic, transportation,telecommunication and distribution industries, where their reliable performance is extremely essential. In this regard, hubs as collection, transfer and distribution points play a critical role in safe system operation. Due to stochastic failures, hubs are not always available which may lead to disruption in flow distribution. In this situation, either flow lost which leads to customer dissatisfaction or a superseded path need to be found, that has additional cost for distributer. This issue is most prominently for time sensitive systems such as postal services, urgency systems and firefighting. Hence, designing a hub location network with respect to reliability concept is an important topic in practice and theory. In this paper, a new hub location model called reliable hub location problem under separate backup hubs (RHLPUSBH) is introduced in which hubs' disruptions are mitigated by backup hubs and alternative routes. RHLPUSBH aims to location of hubs and backup hubs and allocation of other nodes to them so that maximum expected value of transportation cost is minimized. For this purpose, an integer linear program is applied. Due to the complexity of the model, two metaheuristics based on cuckoo optimization algorithm (COA) and genetic algorithm (GA) are developed. Moreover, to evaluate the performance of the suggested methods a computational analysis on AP data set is performed. Obtained results indicate excellent performance of the COA to optimize RHLPUSBH.

Keywords:

Hub location problem , p hub center problem , Reliability , Cuckoo optimization algorithm , Genetic algorithm