Joint Chance Constrained Probabilistic Simple Temporal Networks via Column Generation (Extended Abstract).
Symposium on Combinatorial Search (SOCS)(2022)
摘要
Probabilistic Simple Temporal Networks (PSTN) are used to represent scheduling problems under uncertainty. In a temporal network that is Strongly Controllable (SC) there exists a concrete schedule that is robust to any uncertainty. We solve the problem of determining Chance Constrained PSTN SC as a Joint Chance Constrained optimisation problem via column generation, lifting the usual assumptions of independence and Boole's inequality typically leveraged in PSTN literature. Our approach offers on average a 10 times reduction in cost versus previous methods.
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关键词
probabilistic simple temporal networks,column generation,joint chance
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