Dynamic bundling and pricing for LTL transport requests in Physical Internet
Résumé
This work investigates the dynamic bundling and pricing problem for LTL requests in Physical Internet. From the perspective of carrier, bundling freight transport requests means accepting a package of requests that have synergies on their routes for transport cost reduction. In this work, we consider the situation in which a set of LTL requests with different O-D pairs in a network and carriers should consider request bundling to increase their fill rate and profit. Under combinatorial auction (CA) mechanism, carrier should decide the profitable request bundles that they want to transport and the optimal bidding price to maximize his total profit. Moreover, the future possible requests on the route should also be considered to improve the decision. We propose a mixed integer nonlinear programming (MINLP) model to solve the problem, which optimizes dynamic bundle (route) generation and pricing simultaneously. The model can be used as a decision-making model for carriers to establish real-time transport planning and pricing. A numerical study is constructed to evaluate the feasibility of the proposed model.