A column generation approach for the route planning problem in fourth party logistics

In this paper, we address the route planning problem in fourth party logistics (4PL). The problem calls for the selection of the logistics companies by a 4PL provider to optimize the routes of delivering goods through a transportation network. The concept of 4PL emerged in response to the shortfall in services capabilities of traditional third party logistics and has been proven to be capable of integrating logistics resources in order to fulfill complex transportation demands. A mixed‐integer programming model is established for the planning problem with setup cost and edge cost discount policies which are commonly seen in practice. We propose a column generation approach combined with graph search heuristic to efficiently solve the problem. The good performance in terms of the solution quality and computational efficiency of our approach is shown through extensive numerical experiments on various scales of test instances. Impacts of cost policies on routing decision are also investigated and managerial insights are drawn.