A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems

Metaheuristic optimization algorithms are widely used in solving NP-hard continuous optimization problems. Whereas, in the real world, many optimization problems are discrete. The uncapacitated facility location problem (UFLP) is a pure discrete binary optimization problem. Archimedes optimization a...

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Published in:Düzce Üniversitesi bilim ve teknoloji dergisi (Online) Vol. 10; no. 1; pp. 27 - 38
Main Author: ÇINAR, Ahmet Cevahir
Format: Journal Article
Language:English
Published: Düzce University 31.01.2022
Subjects:
archimedes optimization algorithm
arşimet optimizasyon algoritması
binary optimization
i̇kili optimizasyon
kapasitesiz tesis yerleşimi problemi
uncapacitated facility location problem
ISSN:2148-2446, 2148-2446
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Abstract Metaheuristic optimization algorithms are widely used in solving NP-hard continuous optimization problems. Whereas, in the real world, many optimization problems are discrete. The uncapacitated facility location problem (UFLP) is a pure discrete binary optimization problem. Archimedes optimization algorithm (AOA) is a recently develop metaheuristic optimization algorithm and there is no binary variant of AOA. In this work, 17 transfer functions (TF1-TF17) are used for mapping continuous values to binary values. 17 binary variants of AOA (BAOA1- BAOA17) are proposed for solving UFLPs. 16 to 100-dimensional UFLPs were solved with binary variants of AOA. Stationary and non-stationary transfer functions were compared in terms of solution quality. The non-stationary transfer functions were produced better solutions than stationary transfer functions. Peculiar parameter analyzes for binary optimization problems were performed in the best variant (BAOA9) produced with TF9 transfer function. Meta-sezgisel optimizasyon algoritmaları, NP-zor sürekli optimizasyon problemlerinin çözümünde yaygın olarak kullanılmaktadır. Oysa gerçek dünyada pek çok optimizasyon problemi ayrıktır. Kapasitesiz tesis yerleşimi problemi, saf bir ayrık ikili optimizasyon problemidir. Arşimet optimizasyon algoritması (AOA), yakın zamanda geliştirilmiş bir meta-sezgisel optimizasyon algoritmasıdır ve AOA'nın ikili bir varyantı yoktur. Bu çalışmada, sürekli değerleri ikili değerlere eşlemek için 17 transfer fonksiyonu (TF1-TF17) kullanılmıştır. UFLP'leri çözmek için AOA'nın (BAOA1-BAOA17) 17 ikili varyantı önerilmiştir. 16 ila 100 boyutlu UFLP'ler, AOA'nın ikili varyantları ile çözülmüştür. Durağan ve durağan olmayan transfer fonksiyonları çözüm kalitesi açısından karşılaştırılmıştır. Durağan olmayan transfer fonksiyonları, sabit transfer fonksiyonlarından daha iyi çözümler üretmiştir. İkili optimizasyon problemleri için özel parametre analizleri, TF9 transfer fonksiyonu ile üretilmiş olan en iyi varyantta (BAOA9) gerçekleştirilmiştir.
AbstractList Metaheuristic optimization algorithms are widely used in solving NP-hard continuous optimization problems. Whereas, in the real world, many optimization problems are discrete. The uncapacitated facility location problem (UFLP) is a pure discrete binary optimization problem. Archimedes optimization algorithm (AOA) is a recently develop metaheuristic optimization algorithm and there is no binary variant of AOA. In this work, 17 transfer functions (TF1-TF17) are used for mapping continuous values to binary values. 17 binary variants of AOA (BAOA1- BAOA17) are proposed for solving UFLPs. 16 to 100-dimensional UFLPs were solved with binary variants of AOA. Stationary and non-stationary transfer functions were compared in terms of solution quality. The non-stationary transfer functions were produced better solutions than stationary transfer functions. Peculiar parameter analyzes for binary optimization problems were performed in the best variant (BAOA9) produced with TF9 transfer function. Meta-sezgisel optimizasyon algoritmaları, NP-zor sürekli optimizasyon problemlerinin çözümünde yaygın olarak kullanılmaktadır. Oysa gerçek dünyada pek çok optimizasyon problemi ayrıktır. Kapasitesiz tesis yerleşimi problemi, saf bir ayrık ikili optimizasyon problemidir. Arşimet optimizasyon algoritması (AOA), yakın zamanda geliştirilmiş bir meta-sezgisel optimizasyon algoritmasıdır ve AOA'nın ikili bir varyantı yoktur. Bu çalışmada, sürekli değerleri ikili değerlere eşlemek için 17 transfer fonksiyonu (TF1-TF17) kullanılmıştır. UFLP'leri çözmek için AOA'nın (BAOA1-BAOA17) 17 ikili varyantı önerilmiştir. 16 ila 100 boyutlu UFLP'ler, AOA'nın ikili varyantları ile çözülmüştür. Durağan ve durağan olmayan transfer fonksiyonları çözüm kalitesi açısından karşılaştırılmıştır. Durağan olmayan transfer fonksiyonları, sabit transfer fonksiyonlarından daha iyi çözümler üretmiştir. İkili optimizasyon problemleri için özel parametre analizleri, TF9 transfer fonksiyonu ile üretilmiş olan en iyi varyantta (BAOA9) gerçekleştirilmiştir.
Metaheuristic optimization algorithms are widely used in solving NP-hard continuous optimization problems. Whereas, in the real world, many optimization problems are discrete. The uncapacitated facility location problem (UFLP) is a pure discrete binary optimization problem. Archimedes optimization algorithm (AOA) is a recently develop metaheuristic optimization algorithm and there is no binary variant of AOA. In this work, 17 transfer functions (TF1-TF17) are used for mapping continuous values to binary values. 17 binary variants of AOA (BAOA1- BAOA17) are proposed for solving UFLPs. 16 to 100-dimensional UFLPs were solved with binary variants of AOA. Stationary and non-stationary transfer functions were compared in terms of solution quality. The non-stationary transfer functions were produced better solutions than stationary transfer functions. Peculiar parameter analyzes for binary optimization problems were performed in the best variant (BAOA9) produced with TF9 transfer function.
Author ÇINAR, Ahmet Cevahir
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SubjectTerms archimedes optimization algorithm
arşimet optimizasyon algoritması
binary optimization
i̇kili optimizasyon
kapasitesiz tesis yerleşimi problemi
uncapacitated facility location problem
Title A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems
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