@inproceedings{654608c13ee84344b0a121ef558c73b9,
title = "Simulated metamorphosis - A novel optimizer",
abstract = "This paper presents a novel metaheuristic algorithm, simulated metamorphosis (SM), inspired by the biological concepts of metamorphosis evolution. The algorithm is motivated by the need for interactive, multi-objective, and fast optimization approaches to solving problems with fuzzy conflicting goals and constraints. The algorithm mimics the metamorphosis process, going through three phases: initialization, growth, and maturation. Initialization involves random but guided generation of a candidate solution. After initialization, the algorithm successively goes through two loops, that is, growth and maturation. Computational tests performed on benchmark problems in the literature show that, when compared to competing metaheuristic algorithms, SM is more efficient and effective, producing better solutions within reasonable computation times.",
keywords = "Algorithm, Evolution, Metaheuristics, Metamorphosis, Optimization",
author = "Michael Mutingi and Charles Mbohwa",
year = "2014",
language = "English",
isbn = "9789881925350",
series = "Lecture Notes in Engineering and Computer Science",
publisher = "Newswood Limited",
pages = "924--929",
editor = "Craig Douglas and Ao, {S. I.} and Ao, {S. I.} and Grundfest, {Warren S.} and Jon Burgstone and Craig Douglas and Jon Burgstone and Ao, {S. I.}",
booktitle = "World Congress on Engineering, WCE 2014",
note = "World Congress on Engineering and Computer Science 2014, WCECS 2014 ; Conference date: 22-10-2014 Through 24-10-2014",
}