Best-subset selection procedure

Wang, Hong; Luangkesorn, Louis; Shuman,

doi:10.1109/wsc.2011.6148118

Cited by 15 publications

(12 citation statements)

References 20 publications

(28 reference statements)

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“…11 This takes as inputs 2 parameters: a desired region and an acceptable region (Figure 1). The desired region should represent the difference in performance measures where the 2 policies should be viewed as having practically the same performance.…”

Section: Methodsmentioning

confidence: 99%

“…11 Specifically, we apply the best subset selection (BSS) method to the FRED (A Framework for Reconstructing Epidemiological Dynamic) simulation model of the spread of H1N1 epidemic in Alleghany County, Pennsylvania, with a census-based synthetic population. The BSS method selects good policies that are close in performance to the best policy.…”

mentioning

confidence: 99%

“…The BSS method selects good policies that are close in performance to the best policy. 11 This is in contrast to optimization methods that attempt to find the optimal policy. The BSS method supports health policy makers’ desire to identify a set of alternatives instead of a single “best” policy.…”

mentioning

confidence: 99%

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A Sequential Experimental Design Method to Evaluate a Combination of School Closure and Vaccination Policies to Control an H1N1-Like Pandemic

Luangkesorn

Ghiasabadi

Chhatwal³

2013

Journal of Public Health Management and Practice

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Context During the 2009 H1N1 pandemic, computational agent-based models (ABMs) were extensively used to evaluate interventions to control the spread of emerging pathogens. However, evaluating different possible combinations of interventions using ABMs can be computationally very expensive and time-consuming. Therefore, most policy studies have examined the impact of a single policy decision. Objective To apply a sequential experimental design method with an ABM to analyze policy alternatives composed of a combination of school closure and vaccination policies to provide a set of promising “optimal” combinations of policies to control an H1N1-type epidemic to policy makers. Methods We used an open-source agent-based modeling system, FRED (A Framework for Reconstructing Epidemiological Dynamic), to simulate the spread of an H1N1 epidemic in Alleghany County, Pennsylvania, with a census-based synthetic population. We used an approach called best subset selection method to evaluate 72 alternative policies consisting of a combination of options for school closure threshold, closure duration, Advisory Committee on Immunization Practices prioritization, and second-dose vaccination prioritization policies. Using the attack rate as a performance measure, best subset selection enabled us to eliminate inferior alternatives and identify a small group of alternative policies that could be further evaluated on the basis of other criteria. Results Our sequential design approach to evaluate a combination of alternative mitigation policies leads to a savings in computational effort by a factor of 2 when examining combinations of school closure and vaccination policies. Conclusions Best subset selection demonstrates a substantial reduction in the computational burden of a large-scale ABM in evaluating several alternative policies. Our method also provides policy makers with a set of promising policy combinations for further evaluation based on implementation considerations or other criteria.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

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A Sequential Experimental Design Method to Evaluate a Combination of School Closure and Vaccination Policies to Control an H1N1-Like Pandemic

Luangkesorn

Ghiasabadi

Chhatwal³

2013

Journal of Public Health Management and Practice

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“…In this section, we conduct numerical experiments to test and compare the performance of OCBAm+ with OCBAm, EA and the indifference zone procedure proposed in [27] (IZ_subset in short). We use P{CS} as the empirical performance measure and the asymptotic convergence rate as the theoretical performance measure.…”

Section: Numerical Experimentsmentioning

confidence: 99%

A Simulation Budget Allocation Procedure for Enhancing the Efficiency of Optimal Subset Selection

Zhang

Lee

Chew

et al. 2016

IEEE Trans. Automat. Contr.

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Selecting the optimal subset is highly beneficial to numerous developments in simulation optimization. This paper studies the problem of maximizing the probability of correctly selecting the top-m designs out of k designs under a computing budget constraint. We develop a new procedure which is more efficient and robust than currently existing procedures in the literature. We also provide an analysis on its asymptotic convergence rate. Based on this analysis, we show that our new procedure achieves a higher convergence rate than other procedures under certain conditions. Numerical testing supports our analytical analysis and shows that the new procedure is significantly more efficient and robust.

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“…Further examples of the simulation of casualty health can be found in the literature (Saoud et al, 2006;Rauner et al, 2012;Wang et al, 2012). Casualties in the agent based simulation of Saoud et al (2006) may take one of five discrete health levels, the transition between which is modelled via a series of Markov chains.…”

Section: Progression Simulated But Not Predictedmentioning

confidence: 99%

Modeling Uncertain and Dynamic Casualty Health in Optimization-Based Decision Support for Mass Casualty Incident Response

Wilson

Hawe

Coates

et al. 2013

International Journal of Information Systems for Crisis Response and Management

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Further information on publisher's website:http://dx.doi.org/10. 4018/jiscrm.2013040103 Publisher's copyright statement:Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details.

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Best-subset selection procedure

Cited by 15 publications

References 20 publications

A Sequential Experimental Design Method to Evaluate a Combination of School Closure and Vaccination Policies to Control an H1N1-Like Pandemic

A Sequential Experimental Design Method to Evaluate a Combination of School Closure and Vaccination Policies to Control an H1N1-Like Pandemic

A Simulation Budget Allocation Procedure for Enhancing the Efficiency of Optimal Subset Selection

Modeling Uncertain and Dynamic Casualty Health in Optimization-Based Decision Support for Mass Casualty Incident Response

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