AbstractA mathematical model is introduced to solve a mobile workforce management problem. In such a problem there are a number of tasks to be executed at different locations by various teams. For example, when an electricity utility company has to deal with planned system upgrades and damages caused by storms. The aim is to determine the schedule of the teams in such a way that the overall cost is minimal. The mobile workforce management problem involves scheduling. The following questions should be answered: when to perform a task, how to route vehicles—the vehicle routing problem—and the order the sites should be visited and by which teams. These problems are already complex in themselves. This paper proposes an integrated mathematical programming model formulation, which, by the assignment of its binary variables, can be easily included in heuristic algorithmic frameworks. In the problem specification, a wide range of parameters can be set. This includes absolute and expected time windows for tasks, packing and unpacking in case of team movement, resource utilization, relations between tasks such as precedence, mutual exclusion or parallel execution, and team-dependent travelling and execution times and costs. To make the model able to solve larger problems, an algorithmic framework is also implemented which can be used to find heuristic solutions in acceptable time. This latter solution method can be used as an alternative. Computational performance is examined through a series of test cases in which the most important factors are scaled.
Using an integrated order picking-vehicle routing problem to study the impact of delivery time windows in e-commerce
