The Job Shop Scheduling is a paradigm of Constraint Satisfaction Problems that has interested to researchers over the last years. In this work we propose a Genetic Algorithm hybridized with a local search method that searches over the space of semi-active schedules and a heuristic seeding method that generates active schedules stochastically. We report results from an experimental study over a small set of selected problem instances of common use, and also over a set of big problem instances that clarify the influence of each method in the Genetic Algorithm performance.
['Miguel A. González', 'María R. Sierra', 'Camino R. Vela', 'Ramiro Varela']
Genetic algorithms hybridized with greedy algorithms and local search over the spaces of active and semi-active schedules