Simulation optimization: a review of algorithms and applications
Simulation optimization (SO) refers to the optimization of an objective function subject to
constraints, both of which can be evaluated through a stochastic simulation. To address …
constraints, both of which can be evaluated through a stochastic simulation. To address …
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 …
[LLIBRE][B] Design and analysis of simulation experiments
JPC Kleijnen - 2018 - Springer
This contribution summarizes the design and analysis of experiments with computerized
simulation models. It focuses on two metamodel (surrogate, emulator) types, namely first …
simulation models. It focuses on two metamodel (surrogate, emulator) types, namely first …
Recent advances in ranking and selection
This tutorial provides an overview on recent advances made in ranking and selection (R&S)
for selecting the best simulated system and discusses challenges that still exist in the field …
for selecting the best simulated system and discusses challenges that still exist in the field …
Simulation optimization: a review of algorithms and applications
Simulation optimization refers to the optimization of an objective function subject to
constraints, both of which can be evaluated through a stochastic simulation. To address …
constraints, both of which can be evaluated through a stochastic simulation. To address …
On the convergence rates of expected improvement methods
IO Ryzhov - Operations Research, 2016 - pubsonline.informs.org
We consider a ranking and selection problem with independent normal observations, and
we analyze the asymptotic sampling rates of expected improvement (EI) methods in this …
we analyze the asymptotic sampling rates of expected improvement (EI) methods in this …
Simulation optimization in inventory replenishment: a classification
H Jalali, IV Nieuwenhuyse - Iie Transactions, 2015 - Taylor & Francis
Simulation optimization is increasingly popular for solving complicated and mathematically
intractable business problems. Focusing on academic articles published between 1998 and …
intractable business problems. Focusing on academic articles published between 1998 and …
Advanced tutorial: Input uncertainty and robust analysis in stochastic simulation
H Lam - 2016 Winter Simulation Conference (WSC), 2016 - ieeexplore.ieee.org
Input uncertainty refers to errors caused by a lack of complete knowledge about the
probability distributions used to generate input variates in stochastic simulation. The …
probability distributions used to generate input variates in stochastic simulation. The …
Expert system for predicting reaction conditions: the Michael reaction case
A generic chemical transformation may often be achieved under various synthetic
conditions. However, for any specific reagents, only one or a few among the reported …
conditions. However, for any specific reagents, only one or a few among the reported …
Simulation optimization: A concise overview and implementation guide
Simulation optimization (SO) is the problem of optimization in the presence of objective and
constraint functions that can only be observed via a stochastic simulation. SO, owing to its …
constraint functions that can only be observed via a stochastic simulation. SO, owing to its …