A genetic algorithm for multi-level, multi-machine lot sizing and scheduling

This contribution introduces a mixed{integer programming formulation for the multi{level, multi{machine proportional lot sizing and scheduling problem. It also presents a genetic algorithm to solve that problem. The e ciency of that algorithm is due to an encoding of solutions which uses a two{dimensional matrix representation with non{binary entries rather than a simple bitstring. A computational study reveals that the proposed procedure works amazingly fast and competes with a tabu search approach that has recently been published.