An adjustable robust optimization model for the resource-constrained project scheduling problem with uncertain activity durations |
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| Affiliation: | 1. Institute of Computing Science, Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland;2. Evidera Ltd, London, United Kingdom;1. Engineering Management and Systems Engineering, Missouri University of Science and Technology, 206 Engineering Management 600 W. 14th Street, Rolla, MO, 65409, USA;2. College of Business Administration, University of Missouri-St. Louis, St. Louis, MO, USA;3. Product Change Control Engineer, Caterpillar Inc., Denison, TX, USA;1. Waseda University, Kita-Kyushu, Japan;2. Dalian University of Technology Dalian, China;3. Fuzzy Logic Systems Institute;4. Tokyo University of Science, Japan |
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| Abstract: | ![]()
This paper addresses the resource-constrained project scheduling problem with uncertain activity durations. An adaptive robust optimization model is proposed to derive the resource allocation decisions that minimize the worst-case makespan, under general polyhedral uncertainty sets. The properties of the model are analyzed, assuming that the activity durations are subject to interval uncertainty where the level of robustness is controlled by a protection factor related to the risk aversion of the decision maker. A general decomposition approach is proposed to solve the robust counterpart of the resource-constrained project scheduling problem, further tailored to address the uncertainty set with the protection factor. An extensive computational study is presented on benchmark instances adapted from the PSPLIB. |
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| Keywords: | Project scheduling Resource constraints Robust optimization Benders decomposition |
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