Abordagem metaheurística híbrida para minimização de custos por antecipação e atrasos na produção.

Abstract

Job-Shop Scheduling (JSS) is an optimization problem that involves decision processes regarding the order in which production orders should be executed in a given set of machines and steps. This problem is well known and has received great attention in the literature in recent years. Therefore, this work aims to carry out a study about a variant of JSS, called Job-Shop Scheduling with minimization of costs by earliness and tardiness (JSS-ETC) and to propose efficient algorithms for its resolution. In JSS-ETC, costs and operational adversities caused by earliness and tardiness that occur when there is inaccuracy in the production schedule are considered, seeking to adopt the Just-in-Time philosophy. In this research, two metaheuristics based on Genetic Algorithm and Local Search are presented. The computational experiments presented attest to the effectiveness of the proposed algorithms by performing a benchmark with algorithms found in the literature.