A dynamic service mechanic problem for a housing corporation

We study a dynamic service mechanic problem in which large maintenance activities, known already before the start of the planning period, and emergency incidents, arriving during the planning period, need to be served by the same pool of mechanics. Since not enough own mechanics are available to serve all jobs, the goal is to minimize total expected costs by timely assigning some of the activities to subcontractors. The developed model combines elements of stochastic programming and online optimization: a two-stage recourse model with a dynamic second stage in which a discrete event simulation is applied to generate decisions. A genetic algorithm is used to solve the entire model. Computational results are presented for randomly generated data sets.

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