The complexity of designing and implementing metaheuristics

Ricardo Soto, Broderick Crawford, Rodrigo Olivares, Cristian Galleguillos, Kathleen Crawford, Franklin Johnson, Fernando Paredes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Optimization problems can be found in several real application domains such as engineering, medicine, mathematics, mechanics, physics, mining, games, design, and biology, among others. There exist several techniques to the efficient solving of these problems, which can be organized in two groups: exact and approximate methods. Metaheuristics are one of the most famous and widely used approximate methods for solving optimization problems. Most of them are known for being inspired on interesting behaviors that can be found on the nature, such as the way in which ants, bees and fishes found food, or the way in which fireflies and bats move on the environment. However, solving optimization problems via metaheuristics is not always a simple trip. In this paper, we analyze and discuss from an usability standpoint how the effort needed to design and implement efficient and robust metaheuristics can be conveniently managed and reduced.

Original languageEnglish
Title of host publicationHCI International 2015 – Posters Extended Abstracts - International Conference, HCI International 2015, Proceedings
EditorsConstantine Stephanidis
PublisherSpringer Verlag
Number of pages5
ISBN (Print)9783319213798
StatePublished - 2015
Event17th International Conference on Human Computer Interaction, HCI 2015 - Los Angeles, United States
Duration: 2 Aug 20157 Aug 2015

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929


Conference17th International Conference on Human Computer Interaction, HCI 2015
Country/TerritoryUnited States
CityLos Angeles


  • Local solution
  • Metaheuristics
  • Optimal solution
  • Optimization problems


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