Second-order nearly orthogonal Latin hypercubes for exploring stochastic simulations

Abstract

Naval Postgraduate School, Monterey, USA This paper presents new Latin hypercube designs with minimal correlations between all main, quadratic, and two-way interaction effects for a full second-order model. These new designs facilitate exploratory analysis of stochastic simulation models in which there is considerable a priori uncertainty about the forms of the responses. We focus on understanding the underlying complexities of simulated systems by exploring the input variables' effects on the behavior of simulation responses. These new designs allow us to determine the driving factors, detect interactions between input variables, identify points of diminishing or increasing rates of return, and find thresholds or change points in localized areas. Our proposed designs enable analysts to fit many diverse metamodels to multiple outputs with a single set of runs. Creating these designs is computationally intensive; therefore, several have been cataloged and made available online to experimenters.

Modeling and simulation of future capabilities with an automated computer-aided wargame

“…Another continuous factor, Time Between Sorties, would have made experimentation much more complicated and required a much larger number of runs to examine the impact of the factors on the different MOEs. Works from Cioppa and Lucas, 9 Sanchez and Sanchez, 10 and MacCalman et al 11 are just some designs that can handle a large number of factors and factor levels, as well as mixtures of discrete and continuous factors. For this study, it was unnecessary to implement these more sophisticated experimental designs.…”

Orthogonal second‐order space‐filling designs with insights from simulation experiments to support test planning

“…These include the following: SFSP: Space‐filling sphere‐packing design. FFFD: Flexible fast filling design SFLH: Latin hypercube with optimal spacing. MmLH: Maximin Latin hypercube. NOLH2: second‐order nearly orthogonal Latin hypercube RAND: points generated uniformly in each dimension of a k ‐dimensional unit cube. …”

“…• NOLH2: second-order nearly orthogonal Latin hypercube. 15 • RAND: points generated uniformly in each dimension of a k-dimensional unit cube.…”

Leveraging a design of experiments methodology to enhance impacts of modeling and simulations for engineered resilient systems

“…See MacCalman and MacCalman et al for new state-of-the-art experimental designs that possess the above mentioned design characteristics. 2,10 3.3.2. Determine the number of experiments.…”