@inbook{b6a55ecaecc741ce98715483b5247ea1,
title = "Discrete optimization via simulation",
abstract = "This chapter describes tools and techniques that are useful for optimization via simulation—maximizing or minimizing the expected value of a performance measure of a stochastic simulation—when the decision variables are discrete. Ranking and selection, globally and locally convergent random search and ordinal optimization are covered, along with a collection of “enhancements” that may be applied to many different discrete optimization via simulation algorithms. We also provide strategies for using commercial solvers.",
author = "Jeff HONG and NELSON, {B L} and J XU",
year = "2015",
doi = "10.1007/978-1-4939-1384-8_2",
language = "English",
isbn = "9781493913831",
volume = "216",
series = "International Series in Operations Research and Management Science",
publisher = "Springer New York",
pages = "9--44",
editor = "Fu, {Michael C.}",
booktitle = "International Series in Operations Research and Management Science",
address = "United States",
}