A Two-Level Metaheuristic Algorithm for the Job-Shop Scheduling Problem

Pisut Pongchairerks

Complexity, 2019, vol. 2019, 1-11

Abstract:

This paper proposes a novel two-level metaheuristic algorithm, consisting of an upper-level algorithm and a lower-level algorithm, for the job-shop scheduling problem (JSP). The upper-level algorithm is a novel population-based algorithm developed to be a parameter controller for the lower-level algorithm, while the lower-level algorithm is a local search algorithm searching for an optimal schedule in the solution space of parameterized-active schedules. The lower-level algorithm’s parameters controlled by the upper-level algorithm consist of the maximum allowed length of idle time, the scheduling direction, the perturbation method to generate an initial solution, and the neighborhood structure. The proposed two-level metaheuristic algorithm, as the combination of the upper-level algorithm and the lower-level algorithm, thus can adapt itself for every single JSP instance.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:8683472

DOI: 10.1155/2019/8683472

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