A dynamic empty equipment and crew allocation model for long-haul networks

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A dynamic empty equipment and crew allocation model for long-haul networks

Çalışkan, Cenk / Hall, Randolph W.

AbstractThis research develops a realistic and efficient operational model to optimize empty equipment and crew movements in long-haul trucking networks with consolidation, where returning drivers home within a reasonable amount of time is an important issue. The problem can be stated as follows. On a network of consolidation centers, demand is expressed as a set of trailer-loads that need to be moved between each pair of consolidation centers in each time period and the objective is to optimize trailer, tractor and driver movements while ensuring that drivers return home within a pre-determined period of time. In this paper, a dynamic integer programming model is developed and an efficient approximate solution method is proposed, which involves column generation and branch-and-bound. The algorithm switches from a combination of network and primal simplex to dual simplex to overcome the degeneracy problem, which is very common for dynamic networks. This novel approach enables solving large problems with many intervals. We solved problems with up to 30 nodes and 48 periods successfully by using real data provided by a less-than-truckload company, and by generating statistical forecasts based on the real data.