Mixed integer programming with decomposition to solve a workforce scheduling and routing problemTools Laesanklang, Wasakorn, Landa-Silva, Dario and Castillo-Salazar, J. Arturo (2015) Mixed integer programming with decomposition to solve a workforce scheduling and routing problem. In: International Conference on Operations Research and Enterprise Systems (ICORES 2015), 10-12 January 2015, Lisbon, Portugal. Full text not available from this repository.AbstractWe propose an approach based on mixed integer programming (MIP) with decomposition to solve a workforce scheduling and routing problem, in which a set of workers should be assigned to tasks that are distributed across different geographical locations. This problem arises from a number of home care planning scenarios in the UK, faced by our industrial partner. We present a mixed integer programming model that incorporates important real-world features of the problem such as defined geographical regions and flexibility in the workers? availability. Given the size of the real-world instances, we propose to decompose the problem based on geographical areas. We show that the quality of the overall solution is affected by the ordering in which the sub-problems are tackled. Hence, we investigate different ordering strategies to solve the sub-problems and show that such decomposition approach is a very promising technique to produce high-quality solutions in practical computational times using an exact optimization method.
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