Conference Proceeding Article
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.
Planning and Scheduling. Temporal constraints. Uncertainty
Artificial Intelligence and Robotics | Business | Operations Research, Systems Engineering and Industrial Engineering
Intelligent Systems and Decision Analytics
ICTAI 2005: 17th IEEE international conference on tools with artificial intelligence, 3-6 June 2013
City or Country
LAU, Hoong Chuin; Ou, Thomas; and Sim, Melvyn.
Robust Temporal Constraint Networks. (2005). ICTAI 2005: 17th IEEE international conference on tools with artificial intelligence, 3-6 June 2013. 82-88. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1134