A genetic algorithm for integrating lot-sizing and sequencing in scheduling a capacitated flow line

In this paper we present a genetic algorithm for solving an important but difficult scheduling problem: that of integrating the lot-sizing and sequencing decisions in scheduling a flow line involving sequence dependent setup times, capacity constraints, limited buffer capacity between machines, and due dates. The problem is based on a real world manufacturing facility that is also described. Novel crossover and mutation operators are presented for both the lot-sizing and sequencing parts of the scheduling problem and the performance of the genetic algorithm is compared to a heuristic approach of integration previously shown to have been effective.