Using cache or credit for parallel ranking and selection

H Avci, BL Nelson, E Song, A Wächter - ACM Transactions on Modeling …, 2023 - dl.acm.org
In this article, we focus on ranking and selection procedures that sequentially allocate
replications to systems by applying some acquisition function. We propose an acquisition …

Efficient Learning for Selecting Top- Context-Dependent Designs

G Zhang, S Chen, K Huang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
We consider a simulation optimization problem for context-dependent decision-making,
which aims to determine the top-designs for all contexts. Under a Bayesian framework, we …

Selection of the most probable best

T Kim, KK Kim, E Song - Operations Research, 2024 - pubsonline.informs.org
We consider an expected-value ranking and selection (R&S) problem where all k solutions'
simulation outputs depend on a common parameter whose uncertainty can be modeled by a …

Top-Two Thompson Sampling for Contextual Top-mc Selection Problems

X Shi, Y Peng, G Zhang - arXiv preprint arXiv:2306.17704, 2023 - arxiv.org
We aim to efficiently allocate a fixed simulation budget to identify the top-mc designs for
each context among a finite number of contexts. The performance of each design under a …

Data-Driven Optimal Allocation for Ranking and Selection under Unknown Sampling Distributions

Y Chen - 2023 Winter Simulation Conference (WSC), 2023 - ieeexplore.ieee.org
Ranking and selection (R&S) is the problem of identifying the optimal alternative from
multiple alternatives through sampling them. In the existing R&S literature, sampling …

Let's Do Ranking & Selection

BL Nelson - 2022 Winter Simulation Conference (WSC), 2022 - ieeexplore.ieee.org
Many tutorials and survey papers have been written on ranking & selection because it is
such a useful tool for simulation optimization when the number of feasible solutions or …

Simulation Optimization: Cache and Credit for Parallel Ranking & Selection, and Dice and Slice for High-Dimensional Problems

H Avci - 2024 - search.proquest.com
This dissertation consists of three parts, each proposing a solution method for a different
version of discrete simulation optimization problems: the gradient-based complete expected …