A heuristic rescheduling algorithm for computer-based production scheduling systems

Li, Rong-Kwei; Shyu, Yu Tang; Adiga, Sadashiv

doi:10.1080/00207549308956824

Cited by 75 publications

(34 citation statements)

References 2 publications

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“…A disruption D is defined by its type and a set of corresponding parameters. Typical forms of disruptions (so-called rescheduling factors) are for instance described by Li, Shyu and Adiga (1993) or Vieira, Herrmann and Lin (2003). A more topical set of definitions and classifications of disruptions in the context of the RCPSP are given by Zhu, Bard and Yu (2005).…”

Section: The Extended Rcpspmentioning

confidence: 99%

“…Affected Operations Rescheduling (AOR, see Li, Shyu and Adiga (1993), Abumaizar and Svestka (1997) as well as Huang et al (2006)) can only be applied to job shop problems as the underlying binary tree allows only for one successor on the job and one successor on the resource associated with an activity. Similarly, Matchup Scheduling (MUP, see Bean et al (1991) as well as Akturk and Gorgulu (1999)) is restricted to problems where activities require no more than one resource.…”

Section: Introductionmentioning

confidence: 99%

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Applying Local Rescheduling in response to schedule disruptions

2008

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Section: The Extended Rcpspmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Applying Local Rescheduling in response to schedule disruptions

2008

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“…The most common forms of disruptions affect activity and resource attributes and lead to changes in durations, starting times, availabilities and so forth. Comprehensive overviews and classifications of different types of disruptions can be found in [14], [23] or [38]. solution quickly can also be applied.…”

Section: Overviewmentioning

confidence: 99%

Extending the RCPSP for modeling and solving disruption management problems

2008

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Abstract. This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem for the comprehensive description of disruption management problems. This conceptual framework employs the concept of alternative activities to consider both the temporal shift of activities or the reallocation of resources and switches from one valid process variant to another one. Activities can be serialized or parallelized, process steps can be inserted or removed and durations as well as resource requirements can be modified dynamically during optimization. Focusing on the domain of the aircraft turnaround as the most important airport ground process, we illustrate how the Extended RCPSP (x-RCPSP) can be applied for decision support. A specific evolutionary algorithm is presented that identifies good-quality solutions to relatively large disruption management problems within only a few seconds. The results of the evaluation illustrate fast convergence on good or optimal schedules and serve as a basis for the development of future problem solving algorithms.

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“…Affected Operations Rescheduling (AOR, see [5], [6], [7]) can only be applied to job shop problems, as the underlying binary tree allows only for one job and one resource successor per activity. Similarly, Matchup Scheduling (MUP, see [8], [9]) is restricted to problems where activities require no more than one resource.…”

Section: Introductionmentioning

confidence: 99%

Local Rescheduling - A Novel Approach for Efficient Response to Schedule Disruptions

Kuster

Jannach

Friedrich

2007

2007 IEEE Symposium on Computational Intelligence in Scheduling

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Abstract-Whenever an unforeseen disturbance occurs during the execution of scheduled operations, rescheduling might be necessary: Beside temporal shifts and the allocation of alternative resources, also potential switches from one process variant to another one have typically to be considered. In realistic scenarios of operational disruption management (DM) the high number of potential options makes the provision of online decision support complex. It is thus necessary to significantly reduce the size of the regarded (search) problems which can for instance be achieved by applying methods of partial rescheduling. However, existing approaches such as Affected Operations Rescheduling (AOR) or Matchup Scheduling (MUP) focus on production-specific problems and can not be applied to more generic problem classes. To overcome this limitation, we introduce a novel approach to partial rescheduling in this paper: Local Rescheduling (LRS) is based on the incremental extension of a time window which is regarded for potential schedule modifications. We discuss how this time window can be initialized, extended and used for rescheduling. Moreover, we illustrate the superior performance of LRS in comparison with full rescheduling and MUP.

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A heuristic rescheduling algorithm for computer-based production scheduling systems

Cited by 75 publications

References 2 publications

Applying Local Rescheduling in response to schedule disruptions

Applying Local Rescheduling in response to schedule disruptions

Extending the RCPSP for modeling and solving disruption management problems

Local Rescheduling - A Novel Approach for Efficient Response to Schedule Disruptions

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