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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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 |
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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 |
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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. |
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text |
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LAU, Hoong Chuin Ou, Thomas Sim, Melvyn |
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LAU, Hoong Chuin Ou, Thomas Sim, Melvyn |
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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 |
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Institutional Knowledge at Singapore Management University |
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2005 |
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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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