Joint Chance Constrained Probabilistic Simple Temporal Networks via Column Generation (Extended Abstract).

Symposium on Combinatorial Search (SOCS)(2022)

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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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