Solving the CLSP by a tabu search heuristic

The multi-item, single-level, capacitated, dynamic lot-sizing problem, commonly abbreviated as CLSP, is considered. The problem is cast in a tight mixed-integer programming model (MIP); tight in the sense that the gap between the optimal value of MIP and that of its linear programming relaxation (LP) is small. The LP relaxation of MIP is then solved by column generation. The resulting feasible solution is further improved by adopting the corresponding set-up schedule and re-optimizing variable costs by solving a minimum-cost network flow (trans-shipment) problem. Subsequently, the improved solution is used as a starting solution for a tabu search procedure, with the worth of moves assessed using the same trans-shipment problem. Results of computational testing of benchmark problem instances are presented. They show that the heuristic solutions obtained are effective, in that they are extremely close to the best known solutions. The computational efficiency makes it possible to solve realistically large problem instances routinely on a personal computer; in particular, the solution procedure is most effective, in terms of solution quality, for larger problem instances.