A novel evolutionary computing approach to the job shop scheduling
problem is proposed. The new technique is based on a recent
metaheuristic which, through its nature and mechanisms, manages to
avoid blockage into local optima, which represents a major concern
when designing an algorithm for scheduling.  Furthermore, the aim
of present paper is to find multiple optimal schedules within one
problem and thus bring several options to its managers. The newly
evolutionary approach to the job shop scheduling problem is
validated on an  instance, which is sufficient to be considered
NP-hard. Results demonstrate the success of this first attempt and
prove the promise of the new approach.