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 efficiency 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.