Modified global best artificial bee colony for constrained optimization problems

Bansal, Jagdish Chand; Joshi, Susheel Kumar; Sharma, Harish

doi:10.1016/j.compeleceng.2017.10.021

Cited by 26 publications

(9 citation statements)

References 19 publications

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“…PMS-ABC has obtained good results when used to calculate benchmarks and some engineering problems. C. J. Bansal [30] , one of the other researchers who has modified ABC, introduced the position update formula of PSO into ABC and improved the position update formula of the worker bee and reconnaissance bee to enhance the search ability of the algorithm. After being verified by the benchmark of CEC 2006, the algorithm was also applied to the optimization field of power flow optimization.…”

Section: Related Workmentioning

confidence: 99%

A Modification of the Imperialist Competitive Algorithm With Hybrid Methods for Constrained Optimization Problems

2021

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This paper studies a modification of the imperialist competitive algorithm to solve constrained optimization problems with hybrid methods. The imperialist competitive algorithm is a kind of evolutionary algorithm based on the colonial competition mechanism of imperialism, which is a type of social heuristic optimization algorithm. However, this algorithm needs to be modified because of some problems, including the decreasing number of empires, which leads to easily falling into a local optimum, and a lack of information exchange among countries leading to the search ability being insufficiently strong.To solve these problems and improve the search ability of the algorithm, a newly improved imperialist competitive algorithm with hybrid methods is proposed based on the imperialist competitive algorithm in this paper. In this algorithm, a crossover mechanism is introduced as the empire interaction to boost the information exchange among countries. Two groups of combinatorial operators are constructed in the process of empire assimilation and revolution to improve the algorithm's global and local search ability. Moreover, a step of empire splitting is added based on the imperialist competitive algorithm in which the number of empires is decreased rapidly by empire competition in imperialist competitive algorithm, which leads to a decrease in the population diversity. Then, the proposed algorithm is tested on 12 benchmark functions and 4 engineering problems, and the constraints are addressed by Deb's rules. The results obtained by the proposed algorithm are compared with those of algorithms that have obtained good results in recent years, and it is shown that the proposed method obtains promising and comparable results on the constrained optimization benchmarks in terms of the solution quality and robustness.INDEX TERMS Constrained optimization problems, Hybrid methods, Imperialist competitive algorithm.

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Section: Related Workmentioning

confidence: 99%

A Modification of the Imperialist Competitive Algorithm With Hybrid Methods for Constrained Optimization Problems

2021

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“…Bu yüzden başarıyı arttırmak farklı arama operatörlerinin kullanılması veya algoritmaların birleştirilmesi önerilmiştir [17,18]. Başarının arttırılması için farklı metasezgisellerin farklı operatörler kullanılarak geliştirilmesi ile ilgili literatür oldukça zengindir [19][20][21][22]. Literatüre bakıldığında başarının arttırıldığı görünse de, arama/keşif ve kullanma/geliştirme (sömürü) fazının dengelenmesine ait problemler devam etmektedir [23,24].…”

Section: Gi̇ri̇ş (Introduction)unclassified

Çok boyutlu sırt çantası problemi için adaptif ikili yapay arı kolonisi algoritması (AİYAK)

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Aydın

2021

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

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Optimizasyon algoritmalarının etkinlik ve verimliliği çözüm uzayında aktif arama/keşif ve hızlı hareket etme kabiliyetlerine bağlıdır. Bir algoritmada “arama” ve “kullanma” kabiliyetleri kullanılan komşuluk operatörleri ile doğrudan ilgilidir. Bu kabiliyetleri arttırmak için birden fazla komşuluk operatörü arama süreci içerisinde dâhil edilebilir. Bu çalışmadan çok boyutlu sırt çantası probleminin çözümü için üç adet komşuluk operatörü içeren adaptif ikili yapay arı kolonisi kullanımı önerilmiştir. Çok boyutlu sırt çantası problemi birçok uygulama alanına sahip olan bir NP-zor problemdir. Özellikle büyük boyutlu problem örneklerinin makul sürelerde çözülmesi oldukça güçtür. Önerilen algoritmaya ait en iyi parametre yapılanmasının belirlenmesi için ilk olarak parametre ayarlama deneysel çalışmaları gerçekleştirilmiştir. Önerilen algoritmanın başarısı ve literatürdeki dört farklı yöntem ile üç farklı problem kümesi üzerinde istatistiksel karşılaştırmaları yapılmıştır. Önerilen algoritmanın literatürdeki diğer yöntemlerden daha başarılı sonuçlar ürettiği gösterilmiştir.

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“…Lin (2013) hybridized the genetic algorithm with the rough set theory to evaluate constraints well and solved the constrained optimization problem (Lin, 2013). Apart from these, many swarm-based algorithms have been applied in the literature for the constrained optimization problem (Bansal et al, 2018;Garg, 2016;Runarsson and Yao, 2000;Kohli and Arora, 2017).…”

Section: Introductionmentioning

confidence: 99%

Hybrid the Arithmetic Optimization Algorithm for Constrained Optimization Problems

Baş

2021

Konya Journal of Engineering Sciences

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Since many real-world problems can be designed as optimization problems, heuristic algorithms are increasingly preferred by researchers. The Arithmetic Optimization Algorithm (AOA) is a newly developed heuristic algorithm. It uses four arithmetic operations in its structure. The addition and subtraction operators enhanced the AOA's local search capability, while the multiplication and division operators enhanced the AOA's global search capability. It has been hybridized with the Tree Seed Algorithm (TSA) to increase the success of AOA. Thus, hybrid AOA-TSA (HAOA) has been proposed. The seed production mechanism of TSA is placed in the random walking stage of AOA. New candidate solutions (seeds) have been produced with the arithmetic operators involved in AOA and the candidate solutions have been compared with the existing solutions. Thus, the performance of AOA has increased. In this study, the success of AOA and HAOA was tested in thirteen constrained optimization problems. The success of AOA and HAOA has been tested for their performance in six different population sizes. The Wilcoxon Signed-Rank test was applied to the obtained results and its success has been proved statistically. The results proved the superiority of HAOA. HAOA has been compared with other heuristic methods in the literature and the success of HAOA has been shown. Additionally, AOA and HAOA have also been tested on three different engineering design problems. The results are discussed and evaluated.

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Modified global best artificial bee colony for constrained optimization problems

Cited by 26 publications

References 19 publications

A Modification of the Imperialist Competitive Algorithm With Hybrid Methods for Constrained Optimization Problems

A Modification of the Imperialist Competitive Algorithm With Hybrid Methods for Constrained Optimization Problems

Çok boyutlu sırt çantası problemi için adaptif ikili yapay arı kolonisi algoritması (AİYAK)

Hybrid the Arithmetic Optimization Algorithm for Constrained Optimization Problems

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