Genetic algorithm and local search for just-in-time job-shop scheduling

This paper describes a successful combination of genetic algorithm and local search procedure to find good solutions for just-in-time job-shop scheduling problem with earliness and tardiness penalties. For each job is given a specific order of machines in which its operations must be processed, and each operation has a due date, a processing time, and earliness and tardiness penalties, which are paid if the operation is completed before or after its due date. The problem is very hard to solve to optimality even for small instances, but the proposed genetic algorithm found good solutions for some problem instances, even improving its performance when a local search procedure is invoked as an additional phase. The quality of the solutions is evaluated and compared to a set of instances from the literature, with up to 20 jobs and 10 machines. The proposed algorithm improved the solution value for most of the instances.