An Efficient Morris Method-Based Framework for Simulation Factor Screening

Wen Shi (), Xi Chen () and Jennifer Shang ()
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Wen Shi: School of Business, Central South University, Changsha, Hunan 410083, China;
Xi Chen: Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia 24061;
Jennifer Shang: Business and College of Business Administration, Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, Pennsylvania 15260

INFORMS Journal on Computing, 2019, vol. 31, issue 4, 745-770

Abstract: In this paper, we study the methodological underpinnings of the Morris elementary effects method, a model-free factor-screening technique originally proposed for deterministic simulation experiments, and develop an efficient Morris method–based framework (EMM) for simulation factor screening. Equipped with an efficient cluster-sampling procedure, EMM can simultaneously screen the main and interaction (or nonlinear) effects of all factors and control the overall false discovery rate at a prescribed level. Despite focusing on deterministic simulation experiments, we reveal the connections between EMM (also the Morris method) and other factor-screening methods, such as sequential bifurcation, and examine the resulting implications in the stochastic simulation setting under some commonly stipulated assumptions in design of experiments. Numerical experiments are presented to demonstrate the efficiency and efficacy of EMM.

Keywords: simulation; design of experiments; statistical analysis; factor screening; Morris method (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orijoc:v:31:y:2019:i:4:p:745-770

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