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

Ahmet Cevahir Çınar

doi:10.29130/dubited.876284

TR EN

Kapasitesiz Tesis Yerleşim Problemleri Üzerinde İkili Arşimet Optimizasyon Algoritmalarının Kapsamlı Bir Karşılaştırması

Abstract

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.

Keywords

İkili optimizasyon, Kapasitesiz tesis yerleşimi problemi, Arşimet optimizasyon algoritması

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

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.

Keywords

Binary optimization, Uncapacitated facility location problem, Archimedes optimization algorithm

Thanks

The authors wish to thank Scientific Research Projects Coordinatorship at Selcuk University and The Scientific and Technological Research Council of Turkey for their institutional supports.

References

[1]T. Sağ, "Çok Merkezli Girdap Arama Algoritması," Düzce Üniversitesi Bilim ve Teknoloji Dergisi, vol. 8, no. 2, pp. 1279-1294, 2020.
[2]M. S. Kiran, "TSA: Tree-seed algorithm for continuous optimization," Expert Systems with Applications, vol. 42, no. 19, pp. 6686-6698, 2015.
[3]I. Gungor, B. G. Emiroglu, A. C. Cinar and M. S. Kiran, "Integration search strategies in tree seed algorithm for high dimensional function optimization," International Journal of Machine Learning and Cybernetics, vol. 11, no. 2, pp. 249-267, 2020.
[4]S. A. Uymaz, G. Tezel and E. Yel, "Artificial algae algorithm (AAA) for nonlinear global optimization," Applied Soft Computing, vol. 31, pp. 153-171, 2015.
[5]O. FINDIK, "Bull optimization algorithm based on genetic operators for continuous optimization problems," Turkish Journal of Electrical Engineering & Computer Sciences, vol. 23, 2015.
[6]G. Yildizdan and Ö. K. Baykan, "A novel modified bat algorithm hybridizing by differential evolution algorithm," Expert Systems with Applications, vol. 141, p. 112949, 2020.
[7]H. T. KAHRAMAN, "Rulet Elektromanyetik Alan Optimizasyon (R-EFO) Algoritması," Düzce Üniversitesi Bilim ve Teknoloji Dergisi, vol. 8, no. 1, pp. 69-80, 2020.
[8]E. Kaya, S. A. Uymaz and B. Kocer, "Boosting galactic swarm optimization with ABC," International Journal of Machine Learning and Cybernetics, vol. 10, no. 9, pp. 2401-2419, 2019.
[9]M. N. Demir and Y. Altun, "Otonom Araçla Genetik Algoritma Kullanılarak Haritalama ve Lokasyon," Düzce Üniversitesi Bilim ve Teknoloji Dergisi, vol. 8, no. 1, pp. 654-666, 2020.
[10]A. C. Cinar, "Training Feed-Forward Multi-Layer Perceptron Artificial Neural Networks with a Tree-Seed Algorithm," Arabian Journal for Science and Engineering, vol. 45, no. 12, pp. 10915-10938, 2020.

[11]M. E. Bayrakdar and A. Çalhan, "Artificial bee colony–based spectrum handoff algorithm in wireless cognitive radio networks," International Journal of Communication Systems, vol. 31, no. 5, p. e3495, 2018.
[12]F. A. Hashim, K. Hussain, E. H. Houssein, M. S. Mabrouk and W. Al-Atabany, "Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems," Applied Intelligence, pp. 1-21, 2020.
[13]A. O. Dundar, M. A. Şahman, M. Tekin and M. S. Kıran, "A comparative application regarding the effects of traveling salesman problem on logistics costs," International Journal of Intelligent Systems and Applications in Engineering, vol. 7, no. 4, pp. 207-2015, 2019.
[14]A. C. Cinar, S. Korkmaz and M. S. Kiran, "A discrete tree-seed algorithm for solving symmetric traveling salesman problem," Engineering Science and Technology, an International Journal, vol. 23, no. 4, pp. 879-890, 2020.
[15]H. Hakli and Z. Ortacay, "An improved scatter search algorithm for the uncapacitated facility location problem," Computers & Industrial Engineering, vol. 135, pp. 855-867, 2019.
[16]M. S. Kiran and M. Gündüz, "XOR-based artificial bee colony algorithm for binary optimization," Turkish Journal of Electrical Engineering & Computer Sciences, vol. 21, no. Sup. 2, pp. 2307-2328, 2013.
[17]Y. Çeli̇kbi̇lek, "Facility Location Selection Using Clustering Based Genetic Algorithm," The Journal of International Scientific Researches, vol. 5, no. 2, pp. 90-98, 2020.
[18]M. A. Sahman, A. A. Altun and A. O. Dündar, "The binary differential search algorithm approach for solving uncapacitated facility location problems," Journal of Computational and Theoretical Nanoscience, vol. 14, no. 1, pp. 670-684, 2017.
[19]M. A. Sahman and A. C. Cinar, "Binary tree-seed algorithms with S-shaped and V-shaped transfer functions," International Journal of Intelligent Systems and Applications in Engineering, vol. 7, no. 2, pp. 111-117, 2019.
[20]S. Korkmaz and M. S. Kiran, "An artificial algae algorithm with stigmergic behavior for binary optimization," Applied Soft Computing, vol. 64, pp. 627-640, 2018.
[21]S. Korkmaz, A. Babalik and M. S. Kiran, "An artificial algae algorithm for solving binary optimization problems," International Journal of Machine Learning and Cybernetics, vol. 9, no. 7, pp. 1233-1247, 2018.
[22]M. Aslan, M. Gunduz and M. S. Kiran, "JayaX: Jaya algorithm with xor operator for binary optimization," Applied Soft Computing, vol. 82, p. 105576, 2019.
[23]A. C. Cinar and M. S. Kiran, "Similarity and logic gate-based tree-seed algorithms for binary optimization," Computers & Industrial Engineering, vol. 115, pp. 631-646, 2018.
[24]C. Rorres, "Completing book II of Archimedes’s on floating bodies," The mathematical intelligencer, vol. 26, no. 3, pp. 32-42, 2004.
[25]J. E. Beasley, "OR-Library: distributing test problems by electronic mail," Journal of the operational research society, vol. 41, no. 11, pp. 1069-1072, 1990.

Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Authors

Ahmet Cevahir Çınar ^*
0000-0001-5596-6767
Türkiye

Publication Date

January 31, 2022

Submission Date

February 7, 2021

Acceptance Date

July 5, 2021

Published in Issue

Year 2022 Volume: 10 Number: 1

DOI

https://doi.org/10.29130/dubited.876284

IZ

https://izlik.org/JA69LK69TR

APA

Çınar, A. C. (2022). A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems. Duzce University Journal of Science and Technology, 10(1), 27-38. https://doi.org/10.29130/dubited.876284

AMA

1.Çınar AC. A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems. DUBİTED. 2022;10(1):27-38. doi:10.29130/dubited.876284

Chicago

Çınar, Ahmet Cevahir. 2022. “A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems”. Duzce University Journal of Science and Technology 10 (1): 27-38. https://doi.org/10.29130/dubited.876284.

EndNote

Çınar AC (January 1, 2022) A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems. Duzce University Journal of Science and Technology 10 1 27–38.

IEEE

[1]A. C. Çınar, “A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems”, DUBİTED, vol. 10, no. 1, pp. 27–38, Jan. 2022, doi: 10.29130/dubited.876284.

ISNAD

Çınar, Ahmet Cevahir. “A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems”. Duzce University Journal of Science and Technology 10/1 (January 1, 2022): 27-38. https://doi.org/10.29130/dubited.876284.

JAMA

1.Çınar AC. A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems. DUBİTED. 2022;10:27–38.

MLA

Çınar, Ahmet Cevahir. “A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems”. Duzce University Journal of Science and Technology, vol. 10, no. 1, Jan. 2022, pp. 27-38, doi:10.29130/dubited.876284.

Vancouver

1.Ahmet Cevahir Çınar. A Comprehensive Comparison of Binary Archimedes Optimization Algorithms on Uncapacitated Facility Location Problems. DUBİTED. 2022 Jan. 1;10(1):27-38. doi:10.29130/dubited.876284

Cited By

A Comprehensive Review of Archimedes Optimization Algorithm with its Theory, Variants, Hybridization, and Applications

Archives of Computational Methods in Engineering

https://doi.org/10.1007/s11831-025-10451-0