Algorithms for Scheduling Projects with Generalized Precedence Relations

Reyck, Bert De; Demeulemeester, Erik; Herroelen, Willy

doi:10.1007/978-1-4615-5533-9_4

Cited by 28 publications

(19 citation statements)

References 30 publications

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“…If the payoff of the project proposal lies within the interval [2,5], rejection maximizes the expected value of the following stages. If the income lies within [5,14], order plan a 1 2 ((0, 0), (1, 0)) becomes the best choice. In the first stage, we have f 1 ((0, 1, 1)(0, 1, 0) ((1, 1), (1, 0) , 1), (1, 0))] + 10 a 1 1 = ((0, 1, 0), (0, 0, 0) 0), (1, 0))] + 10 a Given the example's capacity profile, we can choose from three order plans in the first stage.…”

Section: Example For Single-sized Orders and Infinite Maximum Time Lagsmentioning

confidence: 99%

“…Both sources analyze the crucial issues responsible for time delays and cost overruns. De Reyck [14] points out that the resulting analysis will not produce any detailed scheduling information on when to initiate or terminate individual activities or entire projects, but only allows for estimation of the average time spent on a single project. In [29] and [37] the dynamic selection problem is treated as an admission control problem, a known problem within queueing theory.…”

Section: The Dynamic Selection Problemmentioning

confidence: 99%

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Dynamic order acceptance and capacity planning on a single bottleneck resource

Herbots

Herroelen

Leus

2007

Naval Research Logistics

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We present a tactical decision model for order acceptance and capacity planning that maximizes the expected profits from accepted orders, allowing for aggregate regular as well as nonregular capacity. The stream of incoming order arrivals is the main source of uncertainty in dynamic order acceptance and the company only has forecasts of the main properties of the future incoming projects. Project proposals arrive sequentially with deterministic interarrival times and a decision on order acceptance and capacity planning needs to be made each time a proposal arrives and its project characteristics are revealed. We apply stochastic dynamic programming to determine a profit threshold for the accept/reject decision as well as to deterministically allocate a single bottleneck resource to the accepted projects, both with an eye on maximizing the expected revenues within the problem horizon. We derive a number of managerial insights based on an analysis of the influence of project and environmental characteristics on optimal project selection and aggregate capacity usage.

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Section: Example For Single-sized Orders and Infinite Maximum Time Lagsmentioning

confidence: 99%

Section: The Dynamic Selection Problemmentioning

confidence: 99%

Dynamic order acceptance and capacity planning on a single bottleneck resource

Herbots

Herroelen

Leus

2007

Naval Research Logistics

Self Cite

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“…On the one hand, MRCPSP/max is more general than the ResourceConstrained Project Scheduling Problem with minimum and maximum time lags, RCPSP/max (cf. [4], [6], [19], [22]). Here, for each activity only one execution mode is available.…”

Section: Introductionmentioning

confidence: 99%

“…[4], [10]) and an (exact) branch-and-bound-procedure (cf. [12]), the literature on MRCPSP/max is completely void.…”

Section: Introductionmentioning

confidence: 99%

Resource–constrained project scheduling: a heuristic for the multi–mode case

Heilmann

2001

OR Spektrum

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This paper presents a heuristic solution procedure for a very general resource-constrained project scheduling problem. Here, multiple execution modes are available for the individual activities of the project. In addition, minimum as well as maximum time lags between different activities may be given. The objective is to determine a mode and a start time for each activity such that the temporal and resource constraints are met and the project duration is minimized. Project scheduling problems of this type occur e.g. in process industries. The heuristic is a multi-pass priorityrule method with backplanning which is based on an integration approach and embedded in random sampling. Its performance is evaluated within an experimental performance analysis for problem instances of real-life size with 100 activities and up to 5 modes per activity.

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“…Project scheduling in the recent years observed along heuristics, constraint-resources, metaheuristics, and resource-based constraints, consistency tests are furnished [4,14,18]. E.L. Demeulemeester and W.S.…”

Section: Related Workmentioning

confidence: 99%

Dependency Test: Portraying Pearson's Correlation Coefficient Targeting Activities in Project Scheduling

Shafi¹,

Waheed²,

Sanober³

2016

ijacsa

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Abstract-In this paper, we discuss project scheduling with conflicting activity-resources. Several project activities require same resources but, may be scheduled with the certain lapse of time resulting in repeatedly using the same kind of resources for executing dissimilar activities. Due to the frequent usage of same resources multiple times, expenditure become more expensive and project duration extends. The problem is to find out such kind of activities which are developing implicit relations amid them. , we proposed a solution by introducing TVs (Transparent view of Scheduling) model. First, we analyze and enlists activities according to required resources, categorize them and then we segregate dependent and independent activities by indicating a value. Performing Dependency test on activities by using Pearson's Correlation Coefficient (PCC) to calculate the rate of relations among the ordered activities for similar resources. By using this model we can reschedule activities to avoid confusion and disordering of resources without consumption of time and capital.

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Algorithms for Scheduling Projects with Generalized Precedence Relations

Cited by 28 publications

References 30 publications

Dynamic order acceptance and capacity planning on a single bottleneck resource

Dynamic order acceptance and capacity planning on a single bottleneck resource

Resource–constrained project scheduling: a heuristic for the multi–mode case

Dependency Test: Portraying Pearson's Correlation Coefficient Targeting Activities in Project Scheduling

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