DOEPaper1 - Proceedings of the 2005 Winter Simulation...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
Proceedings of the 2005 Winter Simulation Conference M. E. Kuhl, N. M. Steiger, F. B. Armstrong, and J. A. Joines, eds. WORK SMARTER, NOT HARDER: GUIDELINES FOR DESIGNING SIMULATION EXPERIMENTS Susan M. Sanchez Operations Research Department and Graduate School of Business & Public Policy Naval Postgraduate School Monterey, CA 93943-5219, U.S.A. ABSTRACT We present the basic concepts of experimental design, the types of goals it can address, and why it is such an important and useful tool for simulation. A well-designed experiment allows the analyst to examine many more factors than would otherwise be possible, while providing insights that could not be gleaned from trial-and-error approaches or by sampling factors one at a time. We focus on experiments that can cut down the sampling requirements of some classic designs by orders of magnitude, yet make it possible and practical to develop an understanding of a complex simulation model and gain insights into its behavior. Designs that we have found particularly useful for simulation experiments are illustrated using simple simulation models, and we provide links to other resources for those wishing to learn more. Ideally, this tutorial will leave you excited about experimental designs— and prepared to use them—in your upcoming simulation studies. 1 INTRODUCTION The process of building, verifying, and validating a simula- tion model can be arduous, but once it is complete, it’s time to have the model work for you. One extremely effective way of accomplishing this is to use experimental designs to help explore your simulation model. Before undertaking a simulation experiment, it is useful to think about why this the experiment is needed. Simulation analysts and their clients might seek to (i) develop a basic understanding of a particular simulation model or system, (ii) ±nd robust decisions or policies, or (iii) compare the merits of various decisions or policies (Kleijnen et al. 2005). The goal will influence the way the study should be conducted. The Feld called Design of Experiments (DOE) has been around for a long time. Many of the classic experimental designs can be used in simulation studies. We discuss a few in this paper to explain the concepts and motivate the use of experimental design (see also Chapter 12 of Law and Kelton 2000). However, the environments in which real-world experiments are performed can be quite different from the simulation environment. Table 1, adapted from Sanchez and Lucas (2002), lists some of the assumptions made in traditional DOE settings, as well as features that characterize many simulation settings. Three fundamental concepts in DOE are control, repli- cation, and randomization. Control means that the experi- ment is conducted in a systematic manner after explicitly considering potential sources of error, rather than by using a trial-and-error approach. This tutorial should give you a good understanding of controlled experiments. Replication can be viewed as a way to gain enough data to achieve
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 11/13/2010 for the course ISE 680 taught by Professor Santanu during the Spring '10 term at Purdue University Calumet.

Page1 / 14

DOEPaper1 - Proceedings of the 2005 Winter Simulation...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online