Journal article

Algorithm selection for black-box continuous optimization problems: A survey on methods and challenges

Mario A Munoz, Yuan Sun, Michael Kirley, Saman K Halgamuge

Information Sciences | Elsevier | Published : 2015

Abstract

Selecting the most appropriate algorithm to use when attempting to solve a black-box continuous optimization problem is a challenging task. Such problems typically lack algebraic expressions, it is not possible to calculate derivative information, and the problem may exhibit uncertainty or noise. In many cases, the input and output variables are analyzed without considering the internal details of the problem. Algorithm selection requires expert knowledge of search algorithm efficacy and skills in algorithm engineering and statistics. Even with the necessary knowledge and skills, success is not guaranteed. In this paper, we present a survey of methods for algorithm selection in the black-..

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