Scheduling of Resource-Constrained Projects

Klein, Robert

doi:10.1007/978-1-4615-4629-0

Cited by 110 publications

(62 citation statements)

References 260 publications

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“…Beside the pulse and on/off variables described in the Introduction, there are step variables that indicate whether an activity starts at or before a specific point in time (cf. Klein 2000;Bianco and Caramia 2013). Furthermore, Bianco and Caramia (2013) introduce continuous variables that specify the percentage of completion of the activities at each point in time.…”

Section: Mip Formulations For the Rcpspmentioning

confidence: 99%

MIP formulations for an application of project scheduling in human resource management

2016

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In the literature, various discrete-time and continuous-time mixedinteger linear programming (MIP) formulations for project scheduling problems have been proposed. The performance of these formulations has been analyzed based on generic test instances. The objective of this study is to analyze the performance of discrete-time and continuous-time MIP formulations for a real-life application of project scheduling in human resource management. We consider the problem of scheduling assessment centers. In an assessment center, candidates for job positions perform different tasks while being observed and evaluated by assessors. Because these assessors are highly qualified and expensive personnel, the duration of the assessment center should be minimized. Complex rules for assigning assessors to candidates distinguish this problem from other scheduling problems discussed in the literature. We develop two discrete-time and three continuous-time MIP formulations, and we present problem-specific lower bounds. In a comparative study, we analyze the performance of the five MIP formulations on four real-life instances and a set of 240 instances derived from real-life data. The results indicate that good or optimal solutions are obtained for all instances within short computational time. In particular, one of the real-life instances is solved to optimality. Surprisingly, the continuous-time formulations outperform the discrete-time formulations in terms of solution quality.

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Section: Mip Formulations For the Rcpspmentioning

confidence: 99%

MIP formulations for an application of project scheduling in human resource management

2016

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“…This library contains different problem sets for various types of resource constrained project scheduling problems as well as optimal and heuristic solutions. The data sets may be used for the evaluation of solution procedures for single-mode and multi-mode resource-constrained project scheduling problems (RCPSP) [13], [16], [17].…”

Section: Introductionmentioning

confidence: 99%

Variable Neighborhood Simulated Annealing Method and Application for Design

Felinskas¹,

Sakalauskas²

2008

ISARC 2008 - Proceedings From the 25th International Symposium on Automation and Robotics in Construction

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In this paper we discuss about production scheduling. In manufacturing industry, efficient methods to solve resource constrained scheduling problems are needed. The aim is to find such schedule, which would meet the requirements of job priority relations, resource constraints, minimizing it by some criteria. In many cases this criterion is project's finishing time. We consider job scheduling and optimization algorithms related to resources, time and other constraints. In most cases, scheduling problems belongs to complexity class NP. In order to schedule and optimize jobs, we may apply heuristic methods. We explore application of Simulated Annealing (SA) method combined with variable neighborhood to schedule optimization. Computational results are given using data sets from the project scheduling problems library. Efficiency of the algorithm was tested on high performance computing machine.

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“…Nonetheless, singleproject management concepts are by no means irrelevant as they provide a solid basis for multiproject concepts. For excellent introductions to resource constrained single-project scheduling see Kolisch (1995), Klein (2000), Demeulemeester and Herroelen (2002) and Neumann et al (2003). For surveys of solution approaches see e.g.…”

Section: Multi-project Schedulingmentioning

confidence: 99%

“…To get a stable and reliable basis of comparison, all 480 project instances of the J60 set have been solved by Scatter PROGRESS (Klein andScholl 1999, 2000). 400 of these instances could be solved optimally within 3600 s. These 400 instances and the corresponding optimal solutions were used to build a data set containing transfer times.…”

Section: Generating Test Datamentioning

confidence: 99%

A heuristic solution framework for the resource constrained (multi-)project scheduling problem with sequence-dependent transfer times

Krüger

Schöll

2009

European Journal of Operational Research

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We consider the problem of scheduling multiple projects subject to joint resource constraints.All approaches proposed in the literature so far are based on the assumption that resources can be transferred from one project to the other without any expense in time or cost. In many realworld settings this assumption is not realistic. For example, cranes have to be transported to another location and reinstalled there. In order to consider this additional aspect, we generalise the multi-project scheduling problem by additionally including transfer times which represent transportation, installation, adjustment, (re-) learning and other setup activities necessary when a resource is removed from one project and reassigned to another (or from one job to another within the same project).In this paper, we define the modified multi-project scheduling problem with transfer times (called RCMPSPTT), formulate it as an integer linear programme, propose heuristic solution procedures and present results of comprehensive computational experiments.

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Scheduling of Resource-Constrained Projects

Abstract: Scheduling of resource-constrained projects / by Robert Klein. p.cm. --(Operations research/ computer science interfaces series ; OReS 10) Includes bibIiographical references and index. ISBN 978-1-4613-7093-2 ISBN 978-1-4615-4629-0 (eBook)

Cited by 110 publications

References 260 publications

MIP formulations for an application of project scheduling in human resource management

MIP formulations for an application of project scheduling in human resource management

Variable Neighborhood Simulated Annealing Method and Application for Design

A heuristic solution framework for the resource constrained (multi-)project scheduling problem with sequence-dependent transfer times

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