Abstract
A Mixed-Integer Linear Programming (MILP) based heuristic algorithm is proposed to obtain economical schedules for mobile workforce, taking into account travelling, execution and resource utilization costs and other requirements. The problem of mobile workforce management arises when several working teams must be assigned to tasks spread over a geographic area. This means we do not only have to take scheduling and assignment into consideration, but also significant travelling times and costs. The goal is the minimization of total cost while executing the most tasks possible, which involves keeping travelled distances, and hence environmental impacts low. A novel MILP model is proposed, which is capable of handling several factors that may arise in mobile workforce management problems. These factors include time windows for tasks, resource utilization, packing and unpacking times, and precedence, mutual exclusive or parallel execution requirements between tasks. Our solution method involves a MILP model, as well as a heuristic greedy algorithm, which assigns tasks one by one to teams' schedules. This two level approach ensures practically acceptable computational time. Our method is tested over medium-scale case studies.
