Multi-Project Scheduling: Analysis of Project Performance

Kurtulus, Ibrahim S.; Narula, Subhash C.

doi:10.1080/07408178508975272

Cited by 110 publications

(64 citation statements)

References 5 publications

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“…When processed an operation requires certain amounts of capacitated resources. The RCMPSP with the objective of minimizing the sum of the weighted tardiness is treated, e.g., in Patterson [32], Kurtulus and Narula [21], Norbis and Smith [31], Kim and Schniederjans [16], Moccellin [25], Mohanty and Siddiq [27,28], as well as Lawrence and Morton [23]. De Boer et al [9] treat the case where parts have already been assigned to Operations.…”

Section: Multi Project Schedulingmentioning

confidence: 99%

“…If we add constraint (4) to problem (1) - (3), (7) - (9) we obtain the resource constrained multi-project scheduling problem, where for each resource r the available capacity at time instant t has to be allocated to the Operations which are processed at t. The RCMPSP with the objective of minimizing the sum of the weighted tardiness is treated in Patterson [32], Kurtulus and Naruia [21], Norbis and Smith [31], Kim and Schniederjans [16], Moccellin [25], Mohanty and Siddiq [27,28], as well as Lawrence and Morton [23]. As a generalization of the classical job shop scheduling problem, the resource constrained multi-project scheduling problem is an AfP-hard optimization problem.…”

Section: Model Propertiesmentioning

confidence: 99%

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Integrated scheduling, assembly area- and part-assignment for large-scale, make-to-order assemblies

Kolisch

2000

International Journal of Production Economics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The problem of scheduling multiple, large scale, make-to-order assemblies is considered. Beside "classical" precedence-and resource constraints as known from resource constrained project scheduling we take spatial resource and part availability constraints into account. The objective is to minimize the sum of the weighted tardiness. We propose a MlP-model of the problem which is a generalization of three allocation problems. Since the problem is JfP~hard, a list-scheduling heuristic is proposed and evaluated on a set of benchmark instances. Terms of use: Documents in EconStor may

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Section: Multi Project Schedulingmentioning

confidence: 99%

Section: Model Propertiesmentioning

confidence: 99%

Integrated scheduling, assembly area- and part-assignment for large-scale, make-to-order assemblies

Kolisch

2000

International Journal of Production Economics

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“…Several approaches of this class have been proposed in the literature, e.g., Fendley (1968), Kurtulus and Davis (1982), Kurtulus and Narula (1985), Dumond and Mabert (1988), Tsubakitani and Deckro (1990), Lawrence and Morton (1993), Wiley et al (1998), Ash (1999), Lova et al (2000), Shankar and Nagi (1996), and Mendes (2003).…”

Section: Literature Reviewmentioning

confidence: 99%

A genetic algorithm for the resource constrained multi-project scheduling problem

Gonçalves

Mendes²,

Resende

2008

European Journal of Operational Research

265

126

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This paper presents a genetic algorithm for the Resource Constrained Multi-Project Scheduling Problem (RCMPSP). The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.

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“…It is defined as average relative deviation of the realised finishing time from the critical path time over all projects . These objective functions are commonly used in existing literature on the basic multi-project scheduling problem (Pritsker et al 1969, Kurtulus and Davis 1982, Kurtulus and Narula 1985, Lova and Tormos 2001. However, these objectives for scheduling multiple projects should not be taken for granted.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Scheduling in a static environment has been studied amongst others by Fendley (1968), Pritsker et al (1969), Kurtulus and Davis (1982), Kurtulus and Narula (1985), Lawrence and Morton (1985), Lova et al (2000) or Lova and Tormos (2001). All papers apply either a single-or a multi-project approach.…”

Section: Introductionmentioning

confidence: 99%

Managing and modelling general resource transfers in (multi-)project scheduling

Krüger

Schöll

2008

OR Spectrum

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Most approaches to multi-project scheduling are based on the assumption that resources can be transferred between projects without any expense in time and cost. As this assumption often is not realistic, we generalise the multi-project scheduling problem (RCMPSP) by additionally including transfer times and cost. To integrate this aspect, in a first step, we develop a framework for considering resource transfers in single and multi-project environments. It includes managerial approaches to handle resource transfers, a classification of resource transfer types and new roles that resources can take in these transfers. Afterwards, we define the multi-project scheduling problem with transfer times (RCMPSPTT) and formulate it in a basic and an extended version as integer linear programmes. Eventually, it is supplemented for the first time by cost considerations and introduced as resource constrained multi-project scheduling problem with transfer times and cost (RCMPSPTTC). Computational experiments compare the presented managerial approaches and prove the necessity of explicitly considering transfer times in project scheduling. Moreover, the experiments evaluate the presented MIP models and show that specialised solution procedures are vital.

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Multi-Project Scheduling: Analysis of Project Performance

Cited by 110 publications

References 5 publications

Integrated scheduling, assembly area- and part-assignment for large-scale, make-to-order assemblies

Integrated scheduling, assembly area- and part-assignment for large-scale, make-to-order assemblies

A genetic algorithm for the resource constrained multi-project scheduling problem

Managing and modelling general resource transfers in (multi-)project scheduling

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