Güncel metasezgisel optimizasyon algoritmalarının CEC2020 test fonksiyonları ile karşılaştırılması

Altay, Elif Varol; Altay, Osman

doi:10.24012/dumf.1051338

Cited by 6 publications

(2 citation statements)

References 50 publications

(39 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Metaheuristic optimization approaches have been used as a viable alternative to conventional mathematical procedures in order to achieve global or near-global optimal solutions [3]. The aforementioned approaches are very suitable for conducting global searches, as they possess the capability to effectively explore and identify potential places within the search space with a high accuracy degree and efficiency value.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Altay,

Özçevik

2024

CMES

View full text Add to dashboard Cite

Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve. Such design problems are widely experienced in many engineering fields, such as industry, automotive, construction, machinery, and interdisciplinary research. However, there are established optimization techniques that have shown effectiveness in addressing these types of issues. This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues. The algorithms used in the study are listed as: transient search optimization (TSO), equilibrium optimizer (EO), grey wolf optimizer (GWO), moth-flame optimization (MFO), whale optimization algorithm (WOA), slime mould algorithm (SMA), harris hawks optimization (HHO), chimp optimization algorithm (COA), coot optimization algorithm (COOT), multi-verse optimization (MVO), arithmetic optimization algorithm (AOA), aquila optimizer (AO), sine cosine algorithm (SCA), smell agent optimization (SAO), and seagull optimization algorithm (SOA), pelican optimization algorithm (POA), and coati optimization algorithm (CA). As far as we know, there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems. Hence, a remarkable research guideline is presented in the study for researchers working in the fields of engineering and artificial intelligence, especially when applying the optimization methods that have emerged recently. Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.

show abstract

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Altay,

Özçevik

2024

CMES

View full text Add to dashboard Cite

show abstract

“…Bent Cigar function. The second, third, and fourth functions are the multimodal functions Shifted and Rotated Schwefel's, Shifted and Rotated Lunacek bi-Rastrigin, and Expanded Rosenbrock's plus Griewangk's function, respectively[15]. In addition, there are 3 different hybrids and 3 different composition functions with 𝑁 values of 3, 4, and 5, respectively.…”

mentioning

confidence: 99%

Küresel Optimizasyon Problemlerinde Balçık Kalıp Algoritması ve Hibrit Balçık Kalıp Algoritmalarının Performansının İncelenmesi

Altay

2022

DÜMF MD

Self Cite

View full text Add to dashboard Cite

The Slime mould algorithm (SMA) is a relatively new metaheuristic technique that was just presented. While the performance of the newly proposed algorithms gives satisfactory results in optimization problems, combining a recently proposed algorithm with the components of different algorithms improves the performance of SMAs. In recent years, leader SMA (LSMA) and equilibrium optimizer SMA (ESMA) methods, in which SMA is combined with different algorithms, have been proposed. The advantages of the two proposed methods over SMA in different problems are shown. In this study, in order to eliminate the disadvantages of SMA, such as slow convergence rate and local optimum, the performances of the CEC2020 test functions were investigated together with the LSMA and ESMA methods proposed in recent years. The results obtained are statistically analyzed and given in detail in the study.

show abstract

Assessment of Grey Wolf Optimizer and Its Variants on Benchmark Functions

Altay

2023

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

Güncel metasezgisel optimizasyon algoritmalarının CEC2020 test fonksiyonları ile karşılaştırılması

Cited by 6 publications

References 50 publications

A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Küresel Optimizasyon Problemlerinde Balçık Kalıp Algoritması ve Hibrit Balçık Kalıp Algoritmalarının Performansının İncelenmesi

Assessment of Grey Wolf Optimizer and Its Variants on Benchmark Functions

Contact Info

Product

Resources

About