Reliable Designing of Capacitated Logistics Network with Multi Configuration Structure under Disruptions: A Hybrid Heuristic Based Sample Average Approximation Algorithm

We consider the reliable multi configuration capacitated logistics network design problem (RMCLNDP) with system disruptions, concerned with facilities locating, transportation links constructing, and also allocating their limited capacities to the customers in order to satisfy their demands with a minimum expected total cost (including locating costs, link constructing costs, as well as expected transshipment costs in usual and disruption conditions). The motivating application of this class of problem is in capacitated logistics network design with multi configuration (including multi-product, multi-vehicle, and multi-type link) regarding system disruptions simultaneously. The problem is modelled as a mixed integer program. Also, a hybrid heuristic algorithm is proposed. The algorithm, as an efficient approach, is a hybridization of sample average approximation, the LP relaxation, and a two stage decomposing heuristic. The results of a detailed comprehensive computational analysis are also reported. Computational experiments illustrate that the provided algorithm is able to substantially outperform the integer programming approach in terms of both finding and verifying the efficient optimal (or near optimal) solutions at reasonable processing times.