Machine requirements planning and workload assignment using genetic algorithms

This paper presents a genetic approach to determining the optimal number of machines required in a manufacturing system for meeting a specified production schedule. This use of genetic algorithms is illustrated by solving a typical machine requirements planning problem. Comparison of the respective results obtained by using the proposed approach and a standard mixed-integer programming package shows that the proposed approach is indeed an effective means for optimal manufacturing systems design.