title:
 
A Walk into Metaheuristics for Engineering Optimization: Principles, Methods and Recent Trends
publication:
 
IJCIS
volume-issue:   8 - 4
pages:   606 - 636
ISSN:
  1875-6883
DOI:
  doi:10.2991/10.1080/18756891.2015.1046324 (how to use a DOI)
author(s):
 
Ning Xiong, Daniel Molina, Miguel Leon Ortiz, Francisco Herrera
publication date:
 
August 2015
keywords:
 
metaheuristics, optimization methods, trajectory-based optimization, population-based optimization, multimodal optimization, multi-objective optimization, parallel metaheuristics
abstract:
 
Metaheuristics has attained increasing interest for solving complex real-world problems. This paper studies the principles and the state-of-the-art of metaheuristic methods for engineering optimization. Both the classic and emerging approaches to optimization using metaheuristics are reviewed and analyzed. All the methods are discussed in three basic types: trajectory-based, in which in each step a new solution is created from the previous one; multi-trajectory-based, in which a multi-start mechanism is used; and population-based, where multiple new solutions are created considering a population of approximate solutions. We further discuss algorithms and strategies to handle multi-modal and multi-objective optimization tasks as well as methods for parallel implementation of metaheuristic algorithms. Then, different software frameworks for metaheuristics are introduced. Finally, several interesting directions are pointed out as future research trends.
copyright:
 
© The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/
full text: