Desenvolvimento de uma metaheurística para minimização do atraso total em problemas de flow shop com solução não permutacional

Abstract

The scheduling of production is fundamental to optimize the utilization of the resources of a productive process. Coordination of production planning, determining the assignment of tasks to the machines for customer service in a timely delivery. One of the possible configurations of productive systems is through arrangements being these the Flow Shop. In this type of layout or arrangement the jobs pass through the same series of machines, not necessarily in all but always following the same flow without having to go back one step so that their completion is completed. Because it is a computationally complex problem, specialized literature has used metaheuristics to find good solutions. This work describes the implementation of an algorithm based on Iterated Local Search (ILS) metaheuristics to minimize the total delay in flow shop problems with non-permutational solution (NPFS). Considering that the current literature doesn’t present instances in the models necessary for the metaheuristic tests, random instances were developed for its application. Instances were created and later processed into three ILSs each with a different type of perturbation aiming to find the best best result for the type of problem.