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 …
Simulation for manufacturing system design and operation: Literature review and analysis
This paper provides a comprehensive review of discrete event simulation publications
published between 2002 and 2013 with a particular focus on applications in manufacturing …
published between 2002 and 2013 with a particular focus on applications in manufacturing …
[BOOK][B] Surrogates: Gaussian process modeling, design, and optimization for the applied sciences
RB Gramacy - 2020 - taylorfrancis.com
Computer simulation experiments are essential to modern scientific discovery, whether that
be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are …
be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are …
[BOOK][B] Reinforcement Learning and Stochastic Optimization: A Unified Framework for Sequential Decisions: by Warren B. Powell (ed.), Wiley (2022). Hardback. ISBN …
I Halperin - 2022 - Taylor & Francis
What is reinforcement learning? How is reinforcement learning different from stochastic
optimization? And finally, can it be used for applications to quantitative finance for my current …
optimization? And finally, can it be used for applications to quantitative finance for my current …
[BOOK][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 …
A unified framework for stochastic optimization
WB Powell - European Journal of Operational Research, 2019 - Elsevier
Stochastic optimization is an umbrella term that includes over a dozen fragmented
communities, using a patchwork of sometimes overlap** notational systems with …
communities, using a patchwork of sometimes overlap** notational systems with …
[BOOK][B] Simulation-based optimization
A Gosavi - 2015 - Springer
This book is written for students and researchers in the field of industrial engineering,
computer science, operations research, management science, electrical engineering, and …
computer science, operations research, management science, electrical engineering, and …
Multi-information source optimization
We consider Bayesian methods for multi-information source optimization (MISO), in which
we seek to optimize an expensive-to-evaluate black-box objective function while also …
we seek to optimize an expensive-to-evaluate black-box objective function while also …
Practical heteroscedastic Gaussian process modeling for large simulation experiments
We present a unified view of likelihood based Gaussian progress regression for simulation
experiments exhibiting input-dependent noise. Replication plays an important role in that …
experiments exhibiting input-dependent noise. Replication plays an important role in that …
Simulation optimization in the era of Industrial 4.0 and the Industrial Internet
Simulation is an established tool for predicting and evaluating the performance of complex
stochastic systems that are analytically intractable. Recent research in simulation …
stochastic systems that are analytically intractable. Recent research in simulation …