A proactive sampling approach to project scheduling under uncertainty

Uncertainty in activity durations is a key characteristic of many real world scheduling problems in manufacturing, logistics and project management. RCPSP/max with durational uncertainty is a general model that can be used to represent durational uncertainty in a wide variety of scheduling problems...

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Main Authors: Pradeep VARAKANTHAM, FU, Na, LAU, Hoong Chuin
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Language:English
Published: Institutional Knowledge at Singapore Management University 2016
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Online Access:https://ink.library.smu.edu.sg/sis_research/3342
https://ink.library.smu.edu.sg/context/sis_research/article/4344/viewcontent/AProactiveSamplingApproachProject.pdf
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spelling sg-smu-ink.sis_research-43442016-12-27T05:50:04Z A proactive sampling approach to project scheduling under uncertainty Pradeep VARAKANTHAM, FU, Na LAU, Hoong Chuin Uncertainty in activity durations is a key characteristic of many real world scheduling problems in manufacturing, logistics and project management. RCPSP/max with durational uncertainty is a general model that can be used to represent durational uncertainty in a wide variety of scheduling problems where there exist resource constraints. However, computing schedules or execution strategies for RCPSP/max with durational uncertainty is NP-hard and hence we focus on providing approximation methods in this paper. We pro- vide a principled approximation approach based on Sample Average Approximation (SAA) to compute proactive schedules for RCPSP/max with durational uncertainty. We further contribute an extension to SAA for improving scalability significantly without sacrificing on solution quality. Not only is our approach able to compute schedules at comparable runtimes as existing approaches, it also provides lower α-quantile makespan (also referred to as α-robust makespan) values than the best known approach on benchmark problems from the literature. 2016-02-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3342 https://ink.library.smu.edu.sg/context/sis_research/article/4344/viewcontent/AProactiveSamplingApproachProject.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial Intelligence and Robotics Computer Sciences Operations and Supply Chain Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Artificial Intelligence and Robotics
Computer Sciences
Operations and Supply Chain Management
spellingShingle Artificial Intelligence and Robotics
Computer Sciences
Operations and Supply Chain Management
Pradeep VARAKANTHAM,
FU, Na
LAU, Hoong Chuin
A proactive sampling approach to project scheduling under uncertainty
description Uncertainty in activity durations is a key characteristic of many real world scheduling problems in manufacturing, logistics and project management. RCPSP/max with durational uncertainty is a general model that can be used to represent durational uncertainty in a wide variety of scheduling problems where there exist resource constraints. However, computing schedules or execution strategies for RCPSP/max with durational uncertainty is NP-hard and hence we focus on providing approximation methods in this paper. We pro- vide a principled approximation approach based on Sample Average Approximation (SAA) to compute proactive schedules for RCPSP/max with durational uncertainty. We further contribute an extension to SAA for improving scalability significantly without sacrificing on solution quality. Not only is our approach able to compute schedules at comparable runtimes as existing approaches, it also provides lower α-quantile makespan (also referred to as α-robust makespan) values than the best known approach on benchmark problems from the literature.
format text
author Pradeep VARAKANTHAM,
FU, Na
LAU, Hoong Chuin
author_facet Pradeep VARAKANTHAM,
FU, Na
LAU, Hoong Chuin
author_sort Pradeep VARAKANTHAM,
title A proactive sampling approach to project scheduling under uncertainty
title_short A proactive sampling approach to project scheduling under uncertainty
title_full A proactive sampling approach to project scheduling under uncertainty
title_fullStr A proactive sampling approach to project scheduling under uncertainty
title_full_unstemmed A proactive sampling approach to project scheduling under uncertainty
title_sort proactive sampling approach to project scheduling under uncertainty
publisher Institutional Knowledge at Singapore Management University
publishDate 2016
url https://ink.library.smu.edu.sg/sis_research/3342
https://ink.library.smu.edu.sg/context/sis_research/article/4344/viewcontent/AProactiveSamplingApproachProject.pdf
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