A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems

Hernan Pinto; Alvaro Peña; Carlos Maureira; Matías Valenzuela; Gabriel Villavicencio

doi:10.1007/978-3-030-77445-5_27

A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems

Hernan Pinto, Alvaro Peña, Carlos Maureira, Matías Valenzuela, Gabriel Villavicencio

SCHOOL OF CONSTRUCTION ENGINEERING

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

2 Scopus citations

Abstract

In the fields of engineering and science, there are many combinatorial optimization problems. Many of these problems are NP-hard problems, which are difficult to solve with complete techniques. Therefore, the design of binary algorithms based on swarm intelligence continuous metaheuristics is an area of interest in operations research. In this article, we use a general binarization mechanism based on the k-means technique. We apply k-means technique to the firefly algorithm to solve the multidimensional knapsack problem (MKP). Design experiments to prove the practicality of k-means technique in binarization.

Original language	English
Title of host publication	Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021
Editors	Radek Silhavy
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	297-305
Number of pages	9
ISBN (Print)	9783030774448
DOIs	https://doi.org/10.1007/978-3-030-77445-5_27
State	Published - 2021
Event	10th Computer Science Online Conference, CSOC 2021 - Virtual, Online Duration: 1 Apr 2021 → 1 Apr 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	229
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	10th Computer Science Online Conference, CSOC 2021
City	Virtual, Online
Period	1/04/21 → 1/04/21

Keywords

Combinatorial optimization
Knapsack
Metaheuristics
k-means

Access to Document

10.1007/978-3-030-77445-5_27

Cite this

Pinto, H., Peña, A., Maureira, C., Valenzuela, M., & Villavicencio, G. (2021). A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems. In R. Silhavy (Ed.), Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021 (pp. 297-305). (Lecture Notes in Networks and Systems; Vol. 229). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-77445-5_27

Pinto, Hernan ; Peña, Alvaro ; Maureira, Carlos et al. / A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems. Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021. editor / Radek Silhavy. Springer Science and Business Media Deutschland GmbH, 2021. pp. 297-305 (Lecture Notes in Networks and Systems).

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title = "A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems",

abstract = "In the fields of engineering and science, there are many combinatorial optimization problems. Many of these problems are NP-hard problems, which are difficult to solve with complete techniques. Therefore, the design of binary algorithms based on swarm intelligence continuous metaheuristics is an area of interest in operations research. In this article, we use a general binarization mechanism based on the k-means technique. We apply k-means technique to the firefly algorithm to solve the multidimensional knapsack problem (MKP). Design experiments to prove the practicality of k-means technique in binarization.",

keywords = "Combinatorial optimization, Knapsack, Metaheuristics, k-means",

author = "Hernan Pinto and Alvaro Pe{\~n}a and Carlos Maureira and Mat{\'i}as Valenzuela and Gabriel Villavicencio",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 10th Computer Science Online Conference, CSOC 2021 ; Conference date: 01-04-2021 Through 01-04-2021",

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doi = "10.1007/978-3-030-77445-5_27",

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series = "Lecture Notes in Networks and Systems",

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Pinto, H , Peña, A, Maureira, C, Valenzuela, M & Villavicencio, G 2021, A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems. in R Silhavy (ed.), Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021. Lecture Notes in Networks and Systems, vol. 229, Springer Science and Business Media Deutschland GmbH, pp. 297-305, 10th Computer Science Online Conference, CSOC 2021, Virtual, Online, 1/04/21. https://doi.org/10.1007/978-3-030-77445-5_27

A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems. / Pinto, Hernan ; Peña, Alvaro; Maureira, Carlos et al.
Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021. ed. / Radek Silhavy. Springer Science and Business Media Deutschland GmbH, 2021. p. 297-305 (Lecture Notes in Networks and Systems; Vol. 229).

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

TY - GEN

T1 - A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems

AU - Pinto, Hernan

AU - Peña, Alvaro

AU - Maureira, Carlos

AU - Valenzuela, Matías

AU - Villavicencio, Gabriel

PY - 2021

Y1 - 2021

N2 - In the fields of engineering and science, there are many combinatorial optimization problems. Many of these problems are NP-hard problems, which are difficult to solve with complete techniques. Therefore, the design of binary algorithms based on swarm intelligence continuous metaheuristics is an area of interest in operations research. In this article, we use a general binarization mechanism based on the k-means technique. We apply k-means technique to the firefly algorithm to solve the multidimensional knapsack problem (MKP). Design experiments to prove the practicality of k-means technique in binarization.

AB - In the fields of engineering and science, there are many combinatorial optimization problems. Many of these problems are NP-hard problems, which are difficult to solve with complete techniques. Therefore, the design of binary algorithms based on swarm intelligence continuous metaheuristics is an area of interest in operations research. In this article, we use a general binarization mechanism based on the k-means technique. We apply k-means technique to the firefly algorithm to solve the multidimensional knapsack problem (MKP). Design experiments to prove the practicality of k-means technique in binarization.

KW - Combinatorial optimization

KW - Knapsack

KW - Metaheuristics

KW - k-means

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U2 - 10.1007/978-3-030-77445-5_27

DO - 10.1007/978-3-030-77445-5_27

M3 - Conference contribution

AN - SCOPUS:85115834254

SN - 9783030774448

T3 - Lecture Notes in Networks and Systems

SP - 297

EP - 305

BT - Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021

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Pinto H , Peña A, Maureira C, Valenzuela M, Villavicencio G. A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems. In Silhavy R, editor, Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021. Springer Science and Business Media Deutschland GmbH. 2021. p. 297-305. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-77445-5_27

A Machine Learning Firefly Algorithm Applied to the Resource Allocation Problems

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