LAUSR

Abstract The logistics companies should continuously invent novel solutions to oppose fierce competition. Introducing occasional drivers in the context of freight transportation can represent a valuable option. This paper is concerned with reinforcing the distribution capability of a real-life company by using the novel paradigm of crowdshipping, besides employing its fleet of vehicles. Crowdshipping consists involving occasional drivers, which are to be selected from the public through the use of the combinatorial auction paradigm. We propose a mathematical model that integrates the decisions related to the vehicle routing with the winner determination problem for the occasional drivers’ selection. The objective is to minimize the overall transportation cost of using the company’s available fleet plus the cost of employing external drivers. We also propose two heuristic methods to solve real-life distribution instances; one is based on the decomposition method and the other on a cost-comparison greedy approach. The validity of the model, as well as the heuristic methods, has been verified by solving a real case study related to an online bookstore with door-to-door delivery in Oman. Our computational results show savings that reach 30% with respect to the solution implemented by the company.