Genetic Operators Based on Constraint Repair*

In this paper we describe an approach to solve a scheduling problem in the steel making industry with a combination of a constraint repair approach and genetic algorithms. Because several, sometimes conflicting objectives exist in the production of steel, we have proposed a representation of constraint violations and their importance by fuzzy sets (Dorn and Slany 1994). A weighted aggregation of the violations gives us a means to compare schedules. Furthermore, as pointed out by Minton et al. (1990) the strategy to repair constraints in order to achieve better schedules is a good heuristic for large applications. We have therefore developed domain independent genetic operators that apply knowledge of constraint violations. We report on experiments that show the improvement of the combination for our application and draw some conclusions.