QUATRE-PM: QUasi-Affine TRansformation Evolution With Perturbation Mechanism DOI Creative Commons

Junyuan Zhang,

Zhenyu Meng

IEEE Access, Год журнала: 2023, Номер 11, С. 88711 - 88729

Опубликована: Янв. 1, 2023

Differential Evolution(DE) is a widely used technique to tackle complex optimization problems owing its easy-implementation and excellent performance, nevertheless, the inborn weakness of crossover operation has not been solved even in recent state-of-the-art DE algorithms. There are two commonly schemes DE, exponential binomial crossover. The actually combination 1-point 2-point originated with GA, it positional bias because dependence on parameter separation. tackles by separating each dimension separately treating them independently, however, still exists from higher dimensional view, we name selection bias, that reason why QUATRE algorithm was proposed. evolution matrix primary component which solves previous variants suffer adaptation can be able escape some local optima optimization. Therefore, this paper proposes new better adaptations control parameter, moreover, perturbation mechanism firstly proposed for enhancement population diversity. main contributions our summarized as follows. First, generation proposed, obtain landscape objectives help jump out optima. Second, novel parameters also incorporating historical memory reduction. Third, enhance In order validate algorithm, intensive experiments conducted under 88 benchmark functions universal CEC2013, CEC2014, CEC2017 test suites comparison several variants, results support superiority.

Язык: Английский

Dispersed differential hunger games search for high dimensional gene data feature selection DOI
Zhiqing Chen,

Li Xinxian,

Ran Guo

и другие.

Computers in Biology and Medicine, Год журнала: 2023, Номер 163, С. 107197 - 107197

Опубликована: Июнь 21, 2023

Язык: Английский

Процитировано

7
Improved optimal foraging algorithm for global optimization DOI
Chen Ding, Guangyu Zhu

Computing, Год журнала: 2024, Номер 106(7), С. 2293 - 2319

Опубликована: Апрель 17, 2024

Язык: Английский

Процитировано

2
Sine cosine algorithm with communication and quality enhancement: Performance design for engineering problems DOI Creative Commons
Helong Yu,

Zisong Zhao,

Jing Zhou

и другие.

Journal of Computational Design and Engineering, Год журнала: 2023, Номер 10(4), С. 1868 - 1891

Опубликована: Июль 4, 2023

Abstract In recent years, the sine cosine algorithm (SCA) has become one of popular swarm intelligence algorithms due to its simple and convenient structure. However, standard SCA tends fall into local optimum when solving complex multimodal tasks, leading unsatisfactory results. Therefore, this study presents with communication quality enhancement, called CCEQSCA. The proposed includes two enhancement strategies: collaboration strategy (CC) (EQ). algorithm, CC strengthens connection populations by guiding search agents closer range optimal solutions. EQ improves candidate solutions enhance exploitation algorithm. Furthermore, can explore potential in other scopes, thus strengthening ability prevent trapping optimum. To verify capability CCEQSCA, 30 functions from IEEE CEC2017 are analyzed. is compared 5 advanced original 10 variants. outcomes indicate that it dominant over comparison global optimization tasks. work paper also utilized tackle three typical engineering design problems excellent capabilities. It been experimentally demonstrated CCEQSCA works as an effective tool real issues constraints space.

Язык: Английский

Процитировано

6
Anti-sine-cosine atom search optimization (ASCASO): a novel approach for parameter estimation of PV models DOI
Wei Zhou, Pengjun Wang, Xuehua Zhao

и другие.

Environmental Science and Pollution Research, Год журнала: 2023, Номер 30(44), С. 99620 - 99651

Опубликована: Авг. 24, 2023

Язык: Английский

Процитировано

5
Dynamical Sphere Regrouping Particle Swarm Optimization: A Proposed Algorithm for Dealing with PSO Premature Convergence in Large-Scale Global Optimization DOI Creative Commons
Martín Montes Rivera, Carlos Guerrero-Méndez, Daniela López-Betancur

и другие.

Mathematics, Год журнала: 2023, Номер 11(20), С. 4339 - 4339

Опубликована: Окт. 19, 2023

Optimizing large-scale numerical problems is a significant challenge with numerous real-world applications. The optimization process complex due to the multi-dimensional search spaces and possesses several locally optimal regions. In response this issue, various metaheuristic algorithms variations have been developed, including evolutionary swarm intelligence hybrids of different artificial techniques. Previous studies shown that like PSO perform poorly in high-dimensional spaces, even focused on reducing space. However, we propose modified version algorithm called Dynamical Sphere Regrouping (DSRegPSO) avoid stagnation local DSRegPSO based modifies inertial behavior regrouping dynamical sphere mechanism momentum conservation physics effect. These behaviors maintain swarm’s diversity regulate exploration exploitation space while avoiding mechanisms mimic birds, moving particles similar birds when they look for new food source. Additionally, effect mimics how react collisions boundaries their or are looking food. We evaluated by testing 15 optimizing functions up 1000 dimensions CEC’13 benchmark, standard evaluating Large-Scale Global Optimization used Congress Evolutionary Computation, journals. Our proposal improves all variants registered toolkit comparison obtains best result non-separable against algorithms.

Язык: Английский

Процитировано

5
A Multi-Strategy Sparrow Search Algorithm with Selective Ensemble DOI Open Access
Zhendong Wang,

Jianlan Wang,

Dahai Li

и другие.

Electronics, Год журнала: 2023, Номер 12(11), С. 2505 - 2505

Опубликована: Июнь 1, 2023

Aiming at the deficiencies of sparrow search algorithm (SSA), such as being easily disturbed by local optimal and deficient optimization accuracy, a multi-strategy with selective ensemble (MSESSA) is proposed. Firstly, three novel strategies in strategy pool are proposed: variable logarithmic spiral saltation learning enhances global capability, neighborhood-guided accelerates convergence, adaptive Gaussian random walk coordinates exploration exploitation. Secondly, idea adopted to select an appropriate current stage aid priority roulette selection method. In addition, modified boundary processing mechanism adjusts transgressive sparrows’ locations. The relocation method for discoverers alerters conduct large range, based on suboptimal population scroungers better search. Finally, MSESSA tested CEC 2017 suites. function test, Wilcoxon ablation experiment results show that achieves comprehensive performance than 13 other advanced algorithms. four engineering problems, stability, effectiveness, superiority systematically verified, which has significant advantages can reduce design cost.

Язык: Английский

Процитировано

4
A novel differential evolution algorithm based on periodic intervention and systematic regulation mechanisms DOI

Guanyu Yuan,

Gaoji Sun, Libao Deng

и другие.

Applied Intelligence, Год журнала: 2024, Номер 54(22), С. 11779 - 11803

Опубликована: Сен. 2, 2024

Язык: Английский

Процитировано

1
Enhanced honey badger algorithm based on nonlinear adaptive weight and golden sine operator DOI
Parijata Majumdar, Sanjoy Mitra

Neural Computing and Applications, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 18, 2024

Язык: Английский

Процитировано

1
A multi-strategy spider wasp optimizer based on grouping and dimensional symmetry method with a time-varying weight DOI

Zhiyu Feng,

Donglin Zhu,

Huaiyu Guo

и другие.

International Journal of Machine Learning and Cybernetics, Год журнала: 2024, Номер unknown

Опубликована: Май 23, 2024

Язык: Английский

Процитировано

1
An Enhanced Adaptive Differential Evolution Algorithm With Multi-Mutation Schemes and Weighted Control Parameter Setting DOI Creative Commons
Mengnan Tian, Yanhui Meng, Xingshi He

и другие.

IEEE Access, Год журнала: 2023, Номер 11, С. 98854 - 98874

Опубликована: Янв. 1, 2023

Differential evolution (DE) algorithm is one of the most effective and efficient heuristic approaches for solving complex black box problems. But it still easily suffers from premature convergence stagnation. To alleviate these defects, this paper presents a novel DE variant, named enhanced adaptive differential with multi-mutation schemes weighted control parameter setting (MWADE), to further strengthen its search capability. In MWADE, multi-schemes mutation strategy first proposed properly exploit or explore promising information each individual. Herein, whole population are dynamically grouped into three subpopulations according their fitness values performance, different mutant operators various characteristics respectively adopted subpopulation. Meanwhile, in order ensure exploration at later evolutionary stage, weight-controlled suitably assign scale factors vectors. Moreover, random opposition mechanism greedy selection introduced avoid trapping local optima stagnation, an size reduction scheme devised promote effectiveness algorithm. Finally, illustrate performance thirteen typical algorithms compared MWADE on 30 functions IEEE CEC 2017 test suite dimensions, components also investigated. Numerical results indicate that has better performance.

Язык: Английский

Процитировано

3