Review on ranking and selection: A new perspective
In this paper, we briefly review the development of ranking and selection (R&S) in the past
70 years, especially the theoretical achievements and practical applications in the past 20 …
70 years, especially the theoretical achievements and practical applications in the past 20 …
Simulation optimization: a review, new developments, and applications
We provide a descriptive review of the main approaches for carrying out simulation
optimization, and sample some recent algorithmic and theoretical developments in …
optimization, and sample some recent algorithmic and theoretical developments in …
[LLIBRE][B] Bandit algorithms
T Lattimore, C Szepesvári - 2020 - books.google.com
Decision-making in the face of uncertainty is a significant challenge in machine learning,
and the multi-armed bandit model is a commonly used framework to address it. This …
and the multi-armed bandit model is a commonly used framework to address it. This …
[HTML][HTML] Optimal computing budget allocation for the vector evaluated genetic algorithm in multi-objective simulation optimization
Motivated by the vector evaluation genetic algorithm (VEGA), this research develops
simulation budget allocation rules for the VEGA in solving simulation optimization problems …
simulation budget allocation rules for the VEGA in solving simulation optimization problems …
Simple bayesian algorithms for best arm identification
D Russo - Conference on Learning Theory, 2016 - proceedings.mlr.press
This paper considers the optimal adaptive allocation of measurement effort for identifying the
best among a finite set of options or designs. An experimenter sequentially chooses designs …
best among a finite set of options or designs. An experimenter sequentially chooses designs …
Efficient selectivity and backup operators in Monte-Carlo tree search
R Coulom - International conference on computers and games, 2006 - Springer
A Monte-Carlo evaluation consists in estimating a position by averaging the outcome of
several random continuations. The method can serve as an evaluation function at the leaves …
several random continuations. The method can serve as an evaluation function at the leaves …
[LLIBRE][B] Stochastic simulation optimization: an optimal computing budget allocation
CH Chen, LH Lee - 2011 - books.google.com
With the advance of new computing technology, simulation is becoming very popular for
designing large, complex and stochastic engineering systems, since closed-form analytical …
designing large, complex and stochastic engineering systems, since closed-form analytical …
Optimization for simulation: Theory vs. practice
MC Fu - INFORMS Journal on Computing, 2002 - pubsonline.informs.org
Probably one of the most successful interfaces between operations research and computer
science has been the development of discrete-event simulation software. The recent …
science has been the development of discrete-event simulation software. The recent …
A knowledge-gradient policy for sequential information collection
In a sequential Bayesian ranking and selection problem with independent normal
populations and common known variance, we study a previously introduced measurement …
populations and common known variance, we study a previously introduced measurement …
The knowledge-gradient policy for correlated normal beliefs
We consider a Bayesian ranking and selection problem with independent normal rewards
and a correlated multivariate normal belief on the mean values of these rewards. Because …
and a correlated multivariate normal belief on the mean values of these rewards. Because …