Survival of the flexible: explaining the recent popularity of nature-inspired optimization within a rapidly evolving world

• Published in: Computing Vol. 93; no. 2-4; pp. 135 - 146
• Main Author: Whitacre, James M.
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01-12-2011; Springer Nature B.V
• Subjects: Adaptation; Algorithms; Analysis; Artificial Intelligence; Business; Computer Appl. in Administrative Data Processing; Computer Communication Networks; Computer Science; Customization; Decision theory; Design; Evolution; Evolution & development; Genetic algorithms; Heuristic; Heuristic methods; Hypotheses; Information Systems Applications (incl.Internet); Knowledge; Mathematical models; Mathematical programming; Operations research; Optimization; Optimization techniques; Popularity; Software Engineering; Success; Survival; Trends; Utilities; Operations research; Decision theory; 90; Evolutionary algorithms; Nature-inspired meta-heuristics; Optimization; Mathematical programming
• ISSN: 0010-485X; 1436-5057
• DOI: 10.1007/s00607-011-0156-x

Researchers often comment on the popularity and potential of nature-inspired meta-heuristics (NIM), however there has been a paucity of data to directly support the claim that NIM are growing in prominence compared to other optimization techniques. In a companion article published in this special issue, I reported evidence that the use of NIM is not only growing, but indeed has surpassed mathematical optimization techniques (MOT) and other metaheuristics in several metrics related to academic research activity (publication frequency) and commercial activity (patenting frequency). Motivated by these findings, this article reviews several theories of algorithm utility and discusses why these arguments remain unsatisfying. I argue that any explanation of NIM popularity should directly account for the manner in which most NIM success has actually been achieved: through hybridization and customization to specific problems. By taking a problem lifecycle perspective, this paper provides simple yet important insights into how nature-inspired meta-heuristics might derive utility by being flexible. Given global trends in the evolution of business products and services where optimization algorithms are applied, I speculate that highly flexible algorithm frameworks will become increasingly popular within our rapidly changing world.