A two-stage stochastic winner determination model integrating a hybrid mitigation strategy for transportation service procurement auctions

Abstract

Disruption is one of the important and challenging factors in transportation service procurement auctions. Existing winner determination models tend to ignore bidders’ disruption risks and its dire consequences. This paper particularly studies a revised winner determination problem with disruption risks of bidders for a fourth party logistics (4PL) provider to purchase transportation services via combinatorial reverse auctions. Integrating a hybrid mitigation strategy that includes fortification, reservation and outside option policies to deal with disruptions, a new two-stage stochastic winner determination model is constructed. Based on the characteristics of the deterministic equivalent reformulation, a scenario-based approximation approach is developed as solution method. An upper bound can be obtained by using a scenario reduction approach, and a lower bound can be derived by employing a problem-based relaxation method or an efficient dual decomposition Lagrangian relaxation approach. Numerical experiments are conducted to illustrate the effectiveness and applicability of the proposed model and method, since the gap between the upper bound and lower bound is small. Comparison analysis indicates that our strategy is better than some known strategies, and would have a more significant influence on cost minimization of the 4PL as the probability of disruption becomes higher. Managerial implications are drawn for 4PLs to provide high quality of transportation services under disruptions.