Robust Partial Order Schedules for RCPSP/max with Durational Uncertainty. Fu, N., Varakantham, P., & Lau, H. C. In Paper abstract bibtex In this work, we consider RCPSP/max with durational uncertainty. The objective is to compute robust Partial Order Schedules (or, in short POS) with stochastic posteriori quality guarantees that following the POS, project can be finished before a good (ideally, minimum) makespan. Specifically, we developed Benders decomposition algorithm and proposed cut generation scheme based on temporal analysis to solve the robust optimization problem. Compared to the state-of-art, experimental results show effectiveness and efficiency of our proposed approach in accommodating the maximum time lags constraints during robust POS exploration for RCPSP/max with durational uncertainty.
@inproceedings {icaps16-205,
track = {Main Track},
title = {Robust Partial Order Schedules for RCPSP/max with Durational Uncertainty},
url = {http://www.aaai.org/ocs/index.php/ICAPS/ICAPS16/paper/view/13181},
author = {Na Fu and Pradeep Varakantham and Hoong Chuin Lau},
abstract = {In this work, we consider RCPSP/max with durational uncertainty. The objective is to compute robust Partial Order Schedules (or, in short POS) with stochastic posteriori quality guarantees that following the POS, project can be finished before a good (ideally, minimum) makespan. Specifically, we developed Benders decomposition algorithm and proposed cut generation scheme based on temporal analysis to solve the robust optimization problem. Compared to the state-of-art, experimental results show effectiveness and efficiency of our proposed approach in accommodating the maximum time lags constraints during robust POS exploration for RCPSP/max with durational uncertainty.},
keywords = {Scheduling,Scheduling under uncertainty,Constraint reasoning / OR techniques}
}
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