Robust Temporal Constraint Networks

In this paper, we propose the Robust Temporal Constraint Network (RTCN) model for simple temporal constraint networks where activity durations are bounded by random variables. The problem is to determine whether such temporal network can be executed with failure probability less than a given 0 ≤ E ≤...

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Main Authors: LAU, Hoong Chuin, Ou, Thomas, Sim, Melvyn
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語言:English
出版: Institutional Knowledge at Singapore Management University 2005
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https://ink.library.smu.edu.sg/context/sis_research/article/2133/viewcontent/ICTAI05_RobustSTN.pdf
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spelling sg-smu-ink.sis_research-21332018-07-13T02:58:56Z Robust Temporal Constraint Networks LAU, Hoong Chuin Ou, Thomas Sim, Melvyn In this paper, we propose the Robust Temporal Constraint Network (RTCN) model for simple temporal constraint networks where activity durations are bounded by random variables. The problem is to determine whether such temporal network can be executed with failure probability less than a given 0 ≤ E ≤ 1 for each possible instantiation of the random variables, and if so. how one might find a feasible schedule with each given instantiation. The advantage of our model is that one can vary the value of ∊ to control the level of conservativeness of the solution. We present a computationally tractable and efficient approach to solve these RTCN problems. We study the effects the density of temporal constraint networks have on its makespan under different confidence levels. W e also apply RTCN to solve the stochastic project crashing problem. 2005-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1134 info:doi/10.1109/ICTAI.2005.111 https://ink.library.smu.edu.sg/context/sis_research/article/2133/viewcontent/ICTAI05_RobustSTN.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 Planning and Scheduling. Temporal constraints. Uncertainty Artificial Intelligence and Robotics Business Operations Research, Systems Engineering and Industrial Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Planning and Scheduling. Temporal constraints. Uncertainty
Artificial Intelligence and Robotics
Business
Operations Research, Systems Engineering and Industrial Engineering
spellingShingle Planning and Scheduling. Temporal constraints. Uncertainty
Artificial Intelligence and Robotics
Business
Operations Research, Systems Engineering and Industrial Engineering
LAU, Hoong Chuin
Ou, Thomas
Sim, Melvyn
Robust Temporal Constraint Networks
description In this paper, we propose the Robust Temporal Constraint Network (RTCN) model for simple temporal constraint networks where activity durations are bounded by random variables. The problem is to determine whether such temporal network can be executed with failure probability less than a given 0 ≤ E ≤ 1 for each possible instantiation of the random variables, and if so. how one might find a feasible schedule with each given instantiation. The advantage of our model is that one can vary the value of ∊ to control the level of conservativeness of the solution. We present a computationally tractable and efficient approach to solve these RTCN problems. We study the effects the density of temporal constraint networks have on its makespan under different confidence levels. W e also apply RTCN to solve the stochastic project crashing problem.
format text
author LAU, Hoong Chuin
Ou, Thomas
Sim, Melvyn
author_facet LAU, Hoong Chuin
Ou, Thomas
Sim, Melvyn
author_sort LAU, Hoong Chuin
title Robust Temporal Constraint Networks
title_short Robust Temporal Constraint Networks
title_full Robust Temporal Constraint Networks
title_fullStr Robust Temporal Constraint Networks
title_full_unstemmed Robust Temporal Constraint Networks
title_sort robust temporal constraint networks
publisher Institutional Knowledge at Singapore Management University
publishDate 2005
url https://ink.library.smu.edu.sg/sis_research/1134
https://ink.library.smu.edu.sg/context/sis_research/article/2133/viewcontent/ICTAI05_RobustSTN.pdf
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