Integrated Production Planning and Scheduling on Automobile Assembly Lines

We address the closely related problems of production planning and scheduling on mixed model automobile assembly lines. We propose an integrated solution, in which a production plan that is feasible with respect to aggregate capacity constraints is developed and then a sequence that is feasible with respect to this plan is sought. We propose three tabu-search-based algorithms that explore the solution spaces for both problems to different degrees to find a combination of a production plan and schedule that are feasible and that approximately optimize the objective function (involving the overproduction and underproduction of finished automobiles, the set-up cost, the idle times of work-cells on the line, the makespan and the load deviations among work-cells). Simulation is used to evaluate alternative schedules. Stochastic extensions are proposed and the complexities of these algorithms are discussed. Example runs comparing the algorithms are presented for deterministic cases, stochastic cases, types of automobiles, buffer sizes and number of work-cells. The results show that an embedded tabu search algorithm is suitable for solving small scale problems, an alternate tabu search algorithm for the medium scale and a serial tabu search algorithm for the large scale.