Learning-Based Metaheuristic for Scheduling Unrelated Parallel Machines With Uncertain Setup Times

Abstract

Setup time consists of all the activities that need to be completed before the production process takes place. The extant scheduling predominantly relies on simplistic methods, like the average value obtained from historical data, to estimate setup times. However, such methods are incapable of representing the real industry situation, especially when the setup time is subject to significant uncertainties. In this situation, the estimation error increases proportionally to the problem size. This study proposes a Random-Forest-based metaheuristic to minimize the makespan in an Unrelated Parallel Machines Scheduling Problem (UPMSP) with uncertain machine-dependent and job sequence-dependent setup times (MDJSDSTs). Taking the forging industry as an example, the numerical experiments show that the error percentage for the setup time estimation substantially decreases when the proposed approach is applied. This improvement is particularly significant when large-scale problems are sought. Overall, this study highlights the role of advanced analytics in bridging the gap between scheduling theory and practice. INDEX TERMS Scheduling, unrelated parallel machines, setup times, random-forest, metaheuristic.

Advanced discrete firefly algorithm with adaptive mutation‐based neighborhood search for scheduling unrelated parallel machines with sequence‐dependent setup times

“…However, unlike the regular identical parallel machine scheduling problem, where a permutation of jobs for each machine is the only thing needed, the UPMSP with potentially more than one nonrelated machine per stage has to consider the assignment of jobs to machines and the sequence of jobs on each machine. 4 A variant of the unrelated PMS with sequence-dependent setup times addressed in this paper proposes to handle a set of n jobs available at time zero and scheduled on m machines that process jobs at different rates. 5 This problem is hereafter referred to as P S C P | | , where m i j k m , , max…”

“…The UPMSP can be regarded as an extension of the regular parallel scheduling problem. However, unlike the regular identical parallel machine scheduling problem, where a permutation of jobs for each machine is the only thing needed, the UPMSP with potentially more than one nonrelated machine per stage has to consider the assignment of jobs to machines and the sequence of jobs on each machine 4 …”

Minimizing Total Completion Time in Mixed-Blocking Permutation Flowshops

“…First, applying mixed-blocking constraints on different operating environments is a worthwhile research direction to be pursued; job-shop and openshop scheduling are only some examples of this possible research direction. Second, given the significance of setup times in the accuracy of the scheduling outcomes [30], MBPFSP with sequence-dependent setup times is another research direction to pursue. Finally, considering conflicting objectives, like makespan and TCT, within a multi-objective scheme is a promising room for extending MBPFSPs.…”