A survey of ranking, selection, and multiple comparison procedures for discrete-event simulation

Discrete event simulation models are often constructed so that an analyst may compare two or more competing design alternatives. The paper presents a survey of the literature for two widely used statistical methods for selecting the best design from among a finite set of k alternatives: ranking and selection (R&S) and multiple comparison procedures (MCPs). A comprehensive survey of each topic is presented, along with a summary of recent unified R&S-MCP approaches. In addition, an example of the application of B.L. Nelson and F.J. Matejcik's (1995) combined R&S-MCP procedure is given.