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What is Unimodal

Chapter 3
Handbook of Research on Nature-Inspired Computing for Economics and Management
A problem with a single local optimum (that is de facto also the global optimum). Local search algorithms will find the global optimum of a unimodal problem.
Published in Chapter:
Stochastic Optimization Algorithms
P. Collet (Université du Littoral Côte d’Opale, France) and J. Rennard (Grenoble Graduate School of Business, France)
Copyright: © 2007 |Pages: 17
DOI: 10.4018/978-1-59140-984-7.ch003
Abstract
When looking for a solution, deterministic methods have the enormous advantage that they do find global optima. Unfortunately, they are very CPU intensive, and are useless on untractable NP-hard problems that would require thousands of years for cutting-edge computers to explore. In order to get a result, one needs to revert to stochastic algorithms that sample the search space without exploring it thoroughly. Such algorithms can find very good results, without any guarantee that the global optimum has been reached; but there is often no other choice than using them. This chapter is a short introduction to the main methods used in stochastic optimization.
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