Resumen de Repairing infeasibility in scheduling via genetic algorithms
Raul Mencia Cascallana, Carlos Mencía Cascallana, Ramiro Alberto Varela Benvenuto 
Scheduling problems arise in an ever increasing number ofapplication domains. Although efficient algorithms exist for a variety of such problems, sometimes it is necessary to satisfy hard constraints that make the problem unfeasible. In this situation, identifying possible ways of repairing infeasibility represents a task of utmost interest. We consider this scenario in the context of job shop scheduling with a hard makespan constraint and address the problem of finding the largest possible subset of the jobs that can be scheduled within such constraint. To this aim, we develop a genetic algorithm that looks for solutions in the searchspace defined by an efficient solution builder, also proposed in the paper. Experimental results show the suitability of our approach.
