Single-machine scheduling with periodic maintenance to minimize makespan

Ji, Min; He, Yong; Cheng, T.C.E.

doi:10.1016/j.cor.2005.05.034

Cited by 159 publications

(86 citation statements)

References 12 publications

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“…Despite there being some interesting papers dealing simultaneously with a maintenance and a production schedule, most of them consider only one decision criterion (Alardhi et al 2007;Benmansour et al 2011;Ji et al 2007;Sortrakul and Cassady 2007;Su and Tsai 2010). In fact, since these integrated models derive from the original problem of the production schedule, some of these papers still consider only the original objectives such as total weighted expected tardiness.…”

Section: Integrated Production and Maintenance Schedulingmentioning

confidence: 96%

Other Risk, Reliability and Maintenance Decision Problems

Almeida

Cavalcante

Alencar

et al. 2015

International Series in Operations Research &Amp; Management Science

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Abstract:In this chapter, specific problems in risk, reliability and maintenance context are described, such as location of backup units, sequencing of maintenance activities, natural disasters, operation planning of a power system network, integrated production and maintenance scheduling, maintenance team sizing and reliability acceptance tests. This chapter presents a multicriteria decision model with an illustrative application for most of these problems. Amongst the MCDM/A approaches considered for the illustrative applications in this chapter are: Multiattribute utility theory (MAUT), PROMETHEE II, NSGA-II. Regarding the reliability acceptance test an MCDM/A Bayesian approach is presented. For these problems, several aspects have been considered such as: size of population, degree of industrialization, the extent of health services (location of backup units); degree of damage, consumption, electric load, special clients, healthcare services, SAIDI and SAIFI (sequencing of maintenance activities); human, environmental, financial and infrastructure concerns (natural disasters); expected tardiness and maintenance costs (integrated production and maintenance scheduling); waiting time and cost of personnel (maintenance team sizing); probability of accepting equipment not in accordance with the reliability specified by the manufacturer; and delaying the project conclusion (reliability acceptance test). Finally, some aspects of multiobjective optimization are discussed.

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Section: Integrated Production and Maintenance Schedulingmentioning

confidence: 96%

Other Risk, Reliability and Maintenance Decision Problems

Almeida

Cavalcante

Alencar

et al. 2015

International Series in Operations Research &Amp; Management Science

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“…One or several unavailability intervals (maintenance periods) might be considered where their start and end times are either known or decision variables. A number of different combinations of the unavailability intervals and job characteristics have been studied (Lee 1996;Liao and Chen 2003;Akturk et al 2004;Chen 2006;Ji et al 2007;Kovacs and Beck 2007;Xu et al 2010;Yu et al 2014).…”

Section: Integrated Maintenance Planning and Production Schedulingmentioning

confidence: 99%

A two-stage coupled algorithm for an integrated maintenance planning and flowshop scheduling problem with deteriorating machines

Bajestani

Beck

2015

J Sched

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We address a novel integrated maintenance and production scheduling problem in a multi-machine and multi-period production system, considering maintenance as a long-term decision. Deterioration of machines over time decreases production capacity. Since maintenance activities not only improve machine conditions, increasing production capacity, but also take time that cannot be used for production, the challenge is to assign maintenance to periods and to schedule maintenance and production activities within each period to minimize the combined cost of maintenance and lost production over the planning horizon. Motivated by logic-based Benders decomposition, we design an integrated two-stage algorithm to solve the problem. The first stage assigns maintenance to machines and time periods, abstracting the scheduling problem, while the second stage creates a schedule for the current time period. The first stage is then re-solved using feedback from the schedule. This iteration between maintenance planning and scheduling continues until the solution costs in two stages converge. The integrated approach models the interdependencies between maintenance and scheduling decisions in highly coupled processes such as wafer fabrication in the semiconductor manufacturing. Our results demonstrate that the benefit of integrated decision making increases when maintenance is less expensive relative to lost production cost and that a longer horizon for maintenance planning is beneficial when maintenance cost increases.

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“…In addition one may hope better approximation algorithms due to the regular structure of the problem. In the following a subset S of tasks is said to fit before a period j if p(S) ≤ s. If Ona period j is covered by task i then S matches the period if s − δ i ≤ p(S) ≤ s. For the periodic problem with machine unavailability periods and non-resumable jobs, Ji, He and Cheng [11] show that minimizing the makespan can not be approximated within a factor 2. In addition they establish that LPT list schedule has precisely a performance guarantee of 2.…”

Section: Periodic Onasmentioning

confidence: 99%

Single machine scheduling with small operator-non-availability periods

Rapine

Brauner

Finke

et al. 2012

J Sched

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Through an industrial application, we were confronted with the planning of experiments where human intervention of a chemists is required to handle the starting and termination. This gives rise to a new type of scheduling problems, namely problems of finding schedules with time periods when the tasks can neither start nor finish. We consider in this paper the natural case of small periods where the duration of the periods is smaller than any processing time. This assumption corresponds to experiments lasting several days whereas the operator unavailability periods are the week-ends. These problems are analyzed on a single machine with the makespan as criterion.We first prove that, contrary to the case of machine unavailability, the problem with one small operator non-availability period can be solved in polynomial time. We then derive approximation and inapproximability results for the general case of k small unavailability periods. We finally focus on the practical case of periodic and equal small unavailability periods. We prove that this problem is not in FPTAS for more than 3 periods and we derive an FPTAS for the two-period case.

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Single-machine scheduling with periodic maintenance to minimize makespan

Cited by 159 publications

References 12 publications

Other Risk, Reliability and Maintenance Decision Problems

Other Risk, Reliability and Maintenance Decision Problems

A two-stage coupled algorithm for an integrated maintenance planning and flowshop scheduling problem with deteriorating machines

Single machine scheduling with small operator-non-availability periods

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