Flexible Scheduling Through Genetic Algorithms

Abstract

In this paper, we focus on a scheduling problem of a machining center which produces a variety of parts with a monthly plan of process. Some parameters which reflect the decision maker's judgements for due-datas are introduced in the formulation of the objective function. Unfortunately, direct application of genetic algorithms to the formulated scheduling problems does not give acceptable results because a lot of infeasible solutions appear in genetic operations. Thus we propose a genetic algorithm which is suitable for the formulated scheduling problems and demonstrate the efficiency of the proposed algorithm through a number of numerical simulations.