JOB-SHOP WITH GENERIC TIME-LAGS: A HEURISTIC BASED APPROACH

This paper deals with the job-shop scheduling problem with generic time-lags (JSPGTL). This problem is a generalization of the job-shop scheduling problem where extra (minimal and maximal) delays can appear between any operations. To solve the problem we extend the ARP-MD Deppner’s heuristic to tackle this extension providing a new randomized heuristic. And propose a greedy version denoted GREEDY_ARP-MD. The numerical experiments are based on a set of 48 instances including 8 instances based on the flow-shop Carlier’s instances and on the well-known 40 Laurence’sjob-shop instances. The numerical experiments proved that ARP-MD heuristic is time consuming and can be used only for small scale instances. Instances with 10 jobs and 10 machines required several hours to obtain a solution. The greedy version is strongly efficient and can be executed thousands of time per second and so gives solutions for a part of the medium and large scale instances. This work is a step into definition of heuristic for the JSPGTL based on the initial Deppner’s proposal. This sequel study prove that definition of efficient heuristic for definition of solutions is a challenging problem and would require a considerable amount of attention to obtain time saving approaches

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