Technical Papers
Sep 18, 2014

Scheduling Policies for the Stochastic Resource Leveling Problem

Publication: Journal of Construction Engineering and Management
Volume 141, Issue 2

Abstract

When uncertainties come into play, the leveled baseline schedule obtained by solving the deterministic resource leveling problem can hardly be executed as planned and this schedule may even become infeasible. In addition, traditional stochastic methods may also suffer from not being able to produce satisfactorily leveled schedules. Therefore, there is a pressing need for new procedures that are capable of dealing with resource leveling subject to uncertainties. The writers study the resource leveling problem subject to activity durations uncertainty where the usage of renewable resources needs to be leveled over time. Two heuristics for producing scheduling policies are presented with the objective of minimizing the expected sum of the weighted coefficient of variation of the resource usage. The two heuristics represent two different ways of tackling the stochastic resource leveling problem. The first heuristic, a modified version of the Burgess and Killebrew leveling procedure, obtains a scheduling policy by solving the deterministic equivalent of the stochastic resource leveling problem. The second heuristic, a simulation-based tabu search procedure, directly works with the stochastic resource leveling problem. Computational experiments are conducted on the well-known project scheduling problem library (PSPLIB) J90 instances.

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Acknowledgments

The writers thank the reviewers for providing valuable suggestions that have improved the quality of this paper. The research of Hongbo Li is supported by the Research Center for Operations Management of the KU Leuven, the National Natural Science Foundation of China under Grant No. 71271019, and a scholarship from the China Scholarship Council.

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Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 141Issue 2February 2015

History

Received: Feb 27, 2014
Accepted: Aug 19, 2014
Published online: Sep 18, 2014
Published in print: Feb 1, 2015
Discussion open until: Feb 18, 2015

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Postdoctoral Researcher, School of Management, Shanghai Univ., Shanghai 200444, China (corresponding author). E-mail: [email protected]
Professor, School of Economics and Management, Beihang Univ., Beijing 100191, China. E-mail: [email protected]
Erik Demeulemeester [email protected]
Professor, Research Center for Operations Management, Faculty of Business and Economics, KU Leuven, Leuven 3000, Belgium. E-mail: [email protected]

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