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作者：Zacharias, Christos; Liu, Nan; Begen, Mehmet A.
作者单位：University of Miami; Boston College; Western University (University of Western Ontario)
摘要：The simultaneous consideration of appointment day (interday scheduling) and time of day (intraday scheduling) in dynamic scheduling decisions is a theoretical and practical problem that has remained open. We introduce a novel dynamic programming framework that incorporates jointly these scheduling decisions in two timescales. Our model is designed with the intention of bridging the two streams of literature on interday and intraday scheduling and to leverage their latest theoretical developmen...
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作者：Pei, Linda; Nelson, Barry L.; Hunter, Susan R.
作者单位：Northwestern University; Purdue University System; Purdue University
摘要：We reconsider the ranking and selection (R&S) problem in stochastic simulation optimization in light of high-performance, parallel computing, where we take ???R&S??? to mean any procedure that simulates all systems (feasible solutions) to provide some statisti-cal guarantee on the selected systems. We argue that when the number of systems is very large, and the parallel processing capability is also substantial, then neither the standard statistical guarantees such as probability of correct se...
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作者：Qi, Mingyao; Jiang, Ruiwei; Shen, Siqian
作者单位：Tsinghua University; University of Michigan System; University of Michigan
摘要：We study a competitive facility location problem (CFLP), where two firms sequentially open new facilities within their budgets, in order to maximize their market shares of demand that follows a probabilistic choice model. This process is a Stackelberg game and admits a bilevel mixed-integer nonlinear program (MINLP) formulation. We derive an equivalent, single-level MINLP reformulation and exploit the problem structures to derive two valid inequalities based on submodularity and concave overes...
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作者：Chen, Zhi; Kuhn, Daniel; Wiesemann, Wolfram
作者单位：City University of Hong Kong; Imperial College London
摘要：We provide an exact deterministic reformulation for data-driven, chanceconstrained programs over Wasserstein balls. For individual chance constraints as well as joint chance constraints with right-hand-side uncertainty, our reformulation amounts to a mixed-integer conic program. In the special case of a Wasserstein ball with the 1-norm or the ???-norm, the cone is the nonnegative orthant, and the chance-constrained program can be reformulated as a mixed-integer linear program. Our reformulatio...
