Competitive Methods for Multi-Level Lot Sizing and Scheduling: Tabu Search and Randomized Regrets.

This contribution presents two heuristic approaches for multi-level, single-machine lot sizing and scheduling. The first one is a variant of a so-called randomized regret based heuristic which is assumed to be the fastest available method for this particular class of problems. The second approach is a tabu search technique that is competitive with respect to both the run-time performance and the average deviation from the optimum objective function values.

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