Single machine total completion time scheduling problem with workload-dependent maintenance duration

Xu, Dehua; Wan, Long; Liu, Aihua; Yang, Dar-Li

doi:10.1016/j.omega.2014.11.002

Cited by 38 publications

(17 citation statements)

References 26 publications

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“…The maintenance interval or numbers are determined by the job‐dependent ageing effect [20], the position‐dependent ageing effect [21], and machine failure mode [22]. The maintenance duration can be determined by workload [23, 24], starting time of maintenance activity [25], and position‐dependent ageing effect [21]. Variable maintenance is more useful for the dynamic and stochastic machine breakdown environment.…”

Section: Introductionmentioning

confidence: 99%

Single‐machine scheduling problem with flexible maintenance and non‐resumable jobs to minimise makespan

Chen

Huang

Chou

et al. 2020

IET Collaborative Intelligent Manufacturing

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Section: Introductionmentioning

confidence: 99%

Single‐machine scheduling problem with flexible maintenance and non‐resumable jobs to minimise makespan

Chen

Huang

Chou

et al. 2020

IET Collaborative Intelligent Manufacturing

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“…The goal is to utilize the resources optimally while reaching targets. This field has been attracted by many scholars during recent years (Mosheiov and Sidney 2010, Vallada and Ruiz 2011, Shafaei et al 2011, Ullrich 2013, Yang et al 2014, Tayebi Araghi et al 2014, Xu et al 2015, Rabiee et al 2016, Nesello et al 2017. The flow shop problem is an important subject in scheduling.…”

Section: Introductionmentioning

confidence: 99%

A bi-objective simulation-optimization approach for solving a no-wait two stages flexible flow shop scheduling problem with rework ability

Rahmanidoust

Zheng²

2017

IBR

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The paper suggests a new rule; called no-wait process. The rule has two stages, and is a flexible flow shop scheduling. The process is the subject to maximize tardiness while minimizing the makespan. This hybrid flow shop problem is known to be NP-hard. Therefore, we come to first, Non-dominated Sorting Genetic Algorithm (NSGA-II), then, Multi-Objective Imperialist Competitive Algorithm (MOICA) and finally, Pareto Archive Evolutionary Strategy (PAES) as three multi-objective Pareto based metaheuristic optimization methods. They are developed to solve the problem to approximately figure out optimal Pareto front. The method is investigated in several problems that differed in size and terms of relative percentage deviation of performance metrics. The conclusion, developed by this method is the most efficient and practicable algorithm at the end.

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“…Machine breakdown or product quality loss is probable when a machine continues to work unceasingly for a long time. To avoid this situation, preventive maintenance is conducted on the machine which may be periodic or flexible (Xu et al 2015). In a flexible maintenance the earliest and latest start time are determined and the maintenance process is allowed to start during this period.…”

Section: Introductionmentioning

confidence: 99%

JIT single machine scheduling problem with periodic preventive maintenance

et al. 2016

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This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms' parameters and a multiple criterion decision making technique based on the technique for order of preference by similarity to ideal solution is applied to choose the best algorithm. Comparison results confirmed the supremacy of MOPSO to the other algorithms.

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Single machine total completion time scheduling problem with workload-dependent maintenance duration

Cited by 38 publications

References 26 publications

Single‐machine scheduling problem with flexible maintenance and non‐resumable jobs to minimise makespan

Single‐machine scheduling problem with flexible maintenance and non‐resumable jobs to minimise makespan

A bi-objective simulation-optimization approach for solving a no-wait two stages flexible flow shop scheduling problem with rework ability

JIT single machine scheduling problem with periodic preventive maintenance

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