Sep 2026· Natural Resources for Human Health· Vol 6, pp. 352-365· 0 citations· 22 references
Abstract
This study develops a flow-shop scheduling framework for optimizing resource utilization under non-resumable unavailability constraints. These non-resumable interruptions are very common in steel manufacturing industry, chemical processing industry and pharmaceutical industry. Under non-resumable unavailability constraint, if a job is interrupted in mid-processing, then entire work done on the job will be lost and when the machine will be available again then the job has to be started from the scratch. This non resumable interruption can be resolved by two ways either by postponing job’s start time so that it starts processing at the end of unavailable interval on the machine or reschedule jobs so that job complete the processing before the beginning of unavailable interval on the machine. Both corrective strategies will affect the completion time of jobs executing on the current machine and latter indirectly to all downstream machines. In this paper, we have considered n-jobs, 2-machines flow-shop problem having a single non-resumable unavailability constraint on each machine. We have developed an algorithm to obtain an optimal sequence which minimize total elapsed time under non-resumable unavailability constraint. This algorithm is implemented in two steps. At the first step, we find a sequence by applying Modified Johnson’s method to take into consideration the modified completion times that are induced by the non-resumable interruptions. At the second step, we apply Branch-and-Bound method that systematically enumerates the solution space with node pruning to assure global optimality of the sequence. The developed algorithm is illustrated through examples.
This paper investigates a two-machine permutation flow shop in which the second machine is unavailable during one fixed interval $[s,t]$. We consider the non-resumable setting: an operation interrupted by the interval must restart from the beginning after the machine becomes available. The objective is to minimize the...
Hao-Long Lu, Yuan Yuan, Xingwu Liu et al.· 0 citations
Modern manufacturing enterprises are increasingly transitioning to multi-variety, small-batch production. This shift introduces significant scheduling challenges, particularly due to the job hierarchy constraints inherent in assembling multi-level intermediate parts. Furthermore, non-machining preparation times—such as...
We consider the two-machine open-shop scheduling problem in which one machine is unavailable during a fixed interval. We study the resumable setting: an operation interrupted by the unavailability interval may resume, without penalty, when the machine becomes available. The objective is to minimize the makespan. Althou...
Hao-Long Lu, Yuan Yuan, Xingwu Liu et al.· 0 citations
We study the problem of scheduling jobs on a serial-batch machine with the aim of minimising the total weighted late work. In a serial-batch setting, jobs within a batch are processed sequentially, and none are removed from the machine until the last job in the batch completes its processing. The processing time of a b...
Yao-Wen Sang, Nai-Ming Xie, Jian Chen et al.· 0 citations
This work establishes a polynomial equivalence between JSC and a variant of the resource-constrained job shop problem with unit-capacity resources and proposes a genetic algorithm using permutation-with-repetition encoding and active, non-delay, and hybrid schedule evaluation procedures.