An important use for discrete-event simulation models lies in comparing and contrasting competing design alternatives without incurring any physical costs. This article presents a survey of the literature for two widely used classes of 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. Procedures are recommended based on their statistical efficiency and ease of application; guidelines for procedure application are offered.