A hybrid multi-objective immune algorithm for predictive and reactive scheduling

The high productivity of a production process has a major impact on the reduction of the production cost and on a quick response to changing demands. Information about a failure‐free machine operation time obtained in advance allows the users to plan preventive maintenance in order to keep the machine in a good operational condition. The introduction of maintenance work into a schedule reduces the frequency of unpredicted breaks caused by machine failures. It also results in higher productivity and in‐time production. The foregoing of this constitutes the main idea of the predictive scheduling method proposed in the paper. Rescheduling of disrupted operations, with a minimal impact on the stability and robustness of a schedule, is the main idea of the reactive scheduling method proposed. The first objective of the paper is to present a hybrid multi‐objective immune algorithm (H‐MOIA) aided by heuristics: a minimal impact of disrupted operation on the schedule (MIDOS) for predictive scheduling and a minimal impact of rescheduled operation on the schedule (MIROS) for reactive scheduling. The second objective is to compare the H‐MOIA with various methods for predictive and reactive scheduling. The H‐MOIA + MIDOS is compared to two algorithms, identified in reference publications: (1) an algorithm based on priority rules: the least flexible job first (LFJ) and the longest processing time (LPT) (2) an Average Slack Method. The H‐MOIA + MIROS is compared to: (1) an algorithm based on priority rules: the LFJ and LPT and (2) Shifted Gap‐Reduction. This paper presents the research results and computer simulations.