Group Scheduling With Nonperiodical Maintenance and Deteriorating Effects

Abstract

In this paper, we consider single machine group scheduling with non-periodical maintenance and deteriorating effects. Non-periodical maintenance, which has unfixed maintaining interval or the number of jobs in each group is unfixed, results in a variable number of groups. Deteriorating effects lead to longer processing times of which the deterioration index depends on job grouping. This problem is of significance in different production settings and is much more difficult than and general that other simpler single machine group scheduling problems. Making use of historical processing times, we construct the actual processing time model for jobs. We prove that the problem under study is NP-hard. By transforming the optimization objective, properties are discovered and two batchbased heuristics are presented for small size problems. To further improve the effectiveness for large size problems, an iterated greedy algorithm is proposed being its main advantages simplicity and effectiveness. The proposed methods are evaluated over a large number of random instances with calibrated parameters and components. Comprehensive computational and statistical analyses demonstrate the superiority of the methods proposed over adapted existing approaches.

A Reinforcing-Learning-Driven Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance under Learning and Deteriorating Effects

“…[3,5] were among the pioneers that investigated the learning effect in scheduling problems, and this was continued in the literature in hundreds of studies with different machine configurations [6,7]. On the other hand, the deteriorating effect [8,9] is a machineoriented phenomenon appearing after processing tasks are conducted on machines for a long time. The machine performances wear out and therefore additional delays are required to execute the production schedule.…”

Maintenance optimisation for systems with multi-dimensional degradation and imperfect inspections

“…Degradation-based models are established by use of the degradation measurements, which are monitored during system operation (Alaswad and Xiang, 2017;Do et al, 2015;Mo and Xie, 2015). In addition, the degradation-based models are able to characterize the physical failure mechanism and investigate the influence of environmental variations on system degradation processes (Cherkaoui et al, 2018;Deloux et al, 2016;Xu et al, 2019). Degradation-based models have been widely employed to analyze reliability of real systems, e.g., micro-electromechanical systems (MEMS) (Song et al, 2014;Skima et al, 2016), hard disk devices (Ye et al, 2013), and light-emitting diodes (LEDs) (Peng and Tseng, 2009).…”