The complexity of designing and implementing metaheuristics

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

doi:10.1007/978-3-319-21380-4_101

The complexity of designing and implementing metaheuristics

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

SCHOOL OF COMPUTER ENGINEERING

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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 language	English
Title of host publication	HCI International 2015 – Posters Extended Abstracts - International Conference, HCI International 2015, Proceedings
Editors	Constantine Stephanidis
Publisher	Springer Verlag
Pages	593-597
Number of pages	5
ISBN (Print)	9783319213798
DOIs	https://doi.org/10.1007/978-3-319-21380-4_101
State	Published - 2015
Event	17th International Conference on Human Computer Interaction, HCI 2015 - Los Angeles, United States Duration: 2 Aug 2015 → 7 Aug 2015

Publication series

Name	Communications in Computer and Information Science
Volume	528
ISSN (Print)	1865-0929

Conference

Conference	17th International Conference on Human Computer Interaction, HCI 2015
Country/Territory	United States
City	Los Angeles
Period	2/08/15 → 7/08/15

Keywords

Local solution
Metaheuristics
Optimal solution
Optimization problems

Access to Document

10.1007/978-3-319-21380-4_101

Cite this

Soto, R., Crawford, B., Olivares, R., Galleguillos, C., Crawford, K., Johnson, F., & Paredes, F. (2015). The complexity of designing and implementing metaheuristics. In C. Stephanidis (Ed.), HCI International 2015 – Posters Extended Abstracts - International Conference, HCI International 2015, Proceedings (pp. 593-597). (Communications in Computer and Information Science; Vol. 528). Springer Verlag. https://doi.org/10.1007/978-3-319-21380-4_101

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title = "The complexity of designing and implementing metaheuristics",

abstract = "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.",

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author = "Ricardo Soto and Broderick Crawford and Rodrigo Olivares and Cristian Galleguillos and Kathleen Crawford and Franklin Johnson and Fernando Paredes",

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Soto, R , Crawford, B, Olivares, R, Galleguillos, C, Crawford, K, Johnson, F & Paredes, F 2015, The complexity of designing and implementing metaheuristics. in C Stephanidis (ed.), HCI International 2015 – Posters Extended Abstracts - International Conference, HCI International 2015, Proceedings. Communications in Computer and Information Science, vol. 528, Springer Verlag, pp. 593-597, 17th International Conference on Human Computer Interaction, HCI 2015, Los Angeles, United States, 2/08/15. https://doi.org/10.1007/978-3-319-21380-4_101

The complexity of designing and implementing metaheuristics. / Soto, Ricardo ; Crawford, Broderick; Olivares, Rodrigo et al.
HCI International 2015 – Posters Extended Abstracts - International Conference, HCI International 2015, Proceedings. ed. / Constantine Stephanidis. Springer Verlag, 2015. p. 593-597 (Communications in Computer and Information Science; Vol. 528).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Soto, Ricardo

AU - Crawford, Broderick

AU - Olivares, Rodrigo

AU - Galleguillos, Cristian

AU - Crawford, Kathleen

AU - Johnson, Franklin

AU - Paredes, Fernando

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

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Soto R , Crawford B, Olivares R, Galleguillos C, Crawford K, Johnson F et al. The complexity of designing and implementing metaheuristics. In Stephanidis C, editor, HCI International 2015 – Posters Extended Abstracts - International Conference, HCI International 2015, Proceedings. Springer Verlag. 2015. p. 593-597. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-21380-4_101

The complexity of designing and implementing metaheuristics

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