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CQFFA:A Chaotic Quasi-oppositional Farmland Fertility Algorithm for Solving Engineering Optimization Problems

Journal of Bionic Engineering 2023年第1期20卷 158-183页

作者： farhad soleimanian ghareh.h.pogh Mohammad h.Nadimi-Shahraki Saeid Barshandeh Benyamin Abdollahzadeh hoda Zamani Department of Computer Engineering Urmia BranchIslamic Azad UniversityUrmia969Iran Faculty of Computer Engineering Najafabad BranchIslamic Azad UniversityNajafabad517Iran Big Data Research Center Najafabad BranchIslamic Azad UniversityNajafabad517Iran Afagh higher Education Institute Urmia969Iran

Farmland Fertility Algorithm(FFA)is a recent nature-inspired metaheuristic algorithm for solving optimization ***,FFA has some drawbacks:slow convergence and imbalance of diversification(exploration)and intensification(exploitation).An adaptive mechanism in every algorithm can achieve a proper balance between exploration and *** literature shows that chaotic maps are incorporated into metaheuristic algorithms to eliminate these ***,in this paper,twelve chaotic maps have been embedded into FFA to find the best numbers of prospectors to increase the exploitation of the best promising ***,the Quasi-Oppositional-Based Learning(QOBL)mechanism enhances the exploration speed and convergence rate;we name a CQFFA *** improvements have been made in line with the weaknesses of the FFA algorithm because the FFA algorithm has fallen into the optimal local trap in solving some complex problems or does not have sufficient ability in the intensification *** results obtained show that the proposed CQFFA model has been significantly *** is applied to twenty-three widely-used test functions and compared with similar state-of-the-art algorithms statistically and ***,the CQFFA algorithm has evaluated six real-world engineering *** experimental results showed that the CQFFA algorithm outperforms other competitor algorithms.

关键词： Nature-inspired algorithm Farmland fertility algorithm Chaotic maps Quasi Engineering optimization problems

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