Simulation optimization using metamodels
RR Barton - Proceedings of the 2009 winter simulation …, 2009 - ieeexplore.ieee.org
Many iterative optimization methods are designed to be used in conjunction with
deterministic objective functions. These optimization methods can be difficult to apply to an …
deterministic objective functions. These optimization methods can be difficult to apply to an …
Stochastic trust-region response-surface method (STRONG)—A new response-surface framework for simulation optimization
Response surface methodology (RSM) is a widely used method for simulation optimization.
Its strategy is to explore small subregions of the decision space in succession instead of …
Its strategy is to explore small subregions of the decision space in succession instead of …
Better than a petaflop: The power of efficient experimental design
SM Sanchez, H Wan - Proceedings of the 2009 Winter …, 2009 - ieeexplore.ieee.org
Recent advances in high-performance computing have pushed computational capabilities to
a petaflop (a thousand trillion operations per second) in a single computing cluster. This …
a petaflop (a thousand trillion operations per second) in a single computing cluster. This …
Data farming: Methods for the present, opportunities for the future
SM Sanchez - ACM Transactions on Modeling and Computer …, 2020 - dl.acm.org
Data farming is a descriptive metaphor that captures the notion of generating data
purposefully to maximize the information “yield” from simulation models. Large-scale …
purposefully to maximize the information “yield” from simulation models. Large-scale …
History of seeking better solutions, AKA simulation optimization
MC Fu, SG Henderson - 2017 Winter Simulation Conference …, 2017 - ieeexplore.ieee.org
Simulation optimization-arguably the ultimate aim of most simulation users-has had a long
and illustrious history closely tied with the 50 years of the Winter Simulation Conference …
and illustrious history closely tied with the 50 years of the Winter Simulation Conference …
Efficient simulation budget allocation with regression
Simulation can be a very powerful tool to help decision making in many applications;
however, exploring multiple courses of actions can be time consuming. Numerous Ranking …
however, exploring multiple courses of actions can be time consuming. Numerous Ranking …
Clop: Confident local optimization for noisy black-box parameter tuning
R Coulom - Advances in Computer Games, 2011 - Springer
Artificial intelligence in games often leads to the problem of parameter tuning. Some
heuristics may have coefficients, and they should be tuned to maximize the win rate of the …
heuristics may have coefficients, and they should be tuned to maximize the win rate of the …
Simulation optimization of a multi-stage multi-product paint shop line with Response Surface Methodology
Recently, Response Surface Methodology (RSM) has attracted a growing interest, along
with other simulation optimization (SO) techniques, for non-parametric modeling and robust …
with other simulation optimization (SO) techniques, for non-parametric modeling and robust …
A multiobjective stochastic genetic algorithm for the pareto-optimal prioritization scheme design of real-time healthcare resource allocation
Many critical or even life-saving healthcare resources such as cadaveric donor organs are
scarce. Upon procurement of such resources, some priority rule is applied to make the …
scarce. Upon procurement of such resources, some priority rule is applied to make the …
Dynamic modeling of public and private decision‐making for hurricane risk management including insurance, acquisition, and mitigation policy
We develop a computational framework for the stochastic and dynamic modeling of regional
natural catastrophe losses with an insurance industry to support government decision …
natural catastrophe losses with an insurance industry to support government decision …