Article
Computer Science, Artificial Intelligence
Thanh Cuong-Le, Hoang-Le Minh, Samir Khatir, Magd Abdel Wahab, Minh Thi Tran, Seyedali Mirjalili
Summary: In this paper, a new Cuckoo search algorithm NMS-CS is proposed, which outperforms the original CS in convergence rate and accuracy by modifying the step mechanism. Through analysis of 23 benchmark functions, NMS-CS shows superior performance compared to CS. Furthermore, NMS-CS demonstrates good performance on engineering design problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Thermodynamics
Andrzej Frackowiak, Agnieszka Wroblewska, Michal Cialkowski
Summary: This paper presents a concept of solving the inverse heat conduction problem using Trefftz functions and provides two examples to validate the effectiveness of the method.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Xiangbo Qi, Zhonghu Yuan, Yan Song
Summary: Integrating heterogeneous biological-inspired strategies and mechanisms into one algorithm can avoid the shortcomings of single algorithm. The proposed integrated cuckoo search optimizer (ICSO) and multi-objective version MOICSO demonstrate the effectiveness of the integrated mechanism and the superior performance of the algorithm.
PEERJ COMPUTER SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Bilal H. Abed-alguni, Noor Aldeen Alawad, Malek Barhoush, Rafat Hammad
Summary: This paper introduces an exploratory CS algorithm that enhances the exploration capabilities of the original CS algorithm through three modifications, showing better performance in experiments compared to other CS variations and well-known swarm optimization algorithms.
Article
Computer Science, Artificial Intelligence
Wenguan Luo, Xiaobing Yu
Summary: This paper discusses the importance of carbon neutrality in the task of social development and proposes a Reinforcement Learning-based Modified Cuckoo Search algorithm (RLMCS) to solve the economic dispatch problem. Experimental results demonstrate that RLMCS is more competitive and robust in solving standard and valve-point effects economic dispatch problems.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Thermodynamics
Shibin Wan, Kun Wang, Peng Xu, Yajin Huang
Summary: In this paper, a single neural adaptive PID (SNA-PID) inverse method is proposed to estimate the thermal boundary condition. Compared with the traditional PID inverse method, SNA-PID can adaptively adjust the weights of PID parameters, thus improving the tuning effect and anti-interference ability.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Computer Science, Interdisciplinary Applications
F. Mostajeran, R. Mokhtari
Summary: This paper extends a semi-supervised deep neural network method to solve ill-posed backward heat conduction problems, which have long been a computational challenge. The methodology's effectiveness and robustness are demonstrated through various tests, including different boundary conditions, thermal diffusivity factors, and domains. Unlike traditional methods, no regularization technique is required. Simulation results show that this revolutionary strategy can efficiently and accurately extract solution patterns even with up to ten percent noise corruption in the input data. Additionally, as the final time is increased, the method remains efficient in recovering the initial time data, demonstrating its robustness. A comparison with the localized radial basis functions finite difference (RBF-FD) method supports the superiority of the semi-supervised neural network approach.
COMPUTER PHYSICS COMMUNICATIONS
(2022)
Article
Mathematics, Applied
Mohamed Akel, Hillal M. Elshehabey, Ragaa Ahmed
Summary: This article investigates the solvability of a one-dimensional nonhomogeneous multilayer diffusion problem using the M rho,m-transform. By reducing the problem into a sequence of one-layer diffusion problems and applying the M rho,m-transform, an explicit solution is obtained. The results are of general attractiveness and include previous works as special cases.
JOURNAL OF FUNCTION SPACES
(2022)
Article
Computer Science, Artificial Intelligence
Juan Li, Yuan-Hua Yang, Hong Lei, Gai-Ge Wang
Summary: The paper proposes a cuckoo search algorithm with balanced-learning mechanism, which enhances search ability through learning beneficial behaviors and achieves a balance between exploitation and exploration by adaptively adjusting learning factors.
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
(2021)
Article
Engineering, Chemical
Mohammad Hijjawi, Mohammad Alshinwan, Osama A. Khashan, Marah Alshdaifat, Waref Almanaseer, Waleed Alomoush, Harish Garg, Laith Abualigah
Summary: This paper proposes an improved arithmetic optimization algorithm (AOA) called AOACS based on the cuckoo search algorithm to solve engineering optimization problems. AOACS uses cuckoo search algorithm operators to enhance the exploitation operations of AOA and improve convergence ratio. The performance of AOACS is evaluated using benchmark functions and engineering design problems, and compared to state-of-the-art approaches, demonstrating its superior performance.
Article
Computer Science, Artificial Intelligence
Alaa Sheta, Malik Braik, Heba Al-Hiary, Seyedali Mirjalili
Summary: In recent decades, research in Artificial Intelligence (AI) has developed various approaches and algorithms to solve complex optimization problems. This paper utilized and improved a meta-heuristic method called Crow Search Algorithm (CSA) to tackle numerical optimization problems, and evaluated its performance on benchmark functions and engineering design problems.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Nirmal Kumar, Ali Akbar Shaikh, Sanat Kumar Mahato, Asoke Kumar Bhunia
Summary: This paper proposes a hybrid algorithm based on the modified CS algorithm and AGQPSO algorithm to solve differential equations problems. By transforming the differential equations problems into optimization problems and optimizing the algorithms accordingly, the algorithm has been successfully applied to multiple benchmark problems and first-order, second-order initial value problems, and boundary value problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Hamid Reza Rafat Zaman, Farhad Soleimanian Gharehchopogh
Summary: This paper introduces the advantages and disadvantages of particle swarm optimization (PSO) and backtracking search optimization algorithm (BSA), proposes an improved algorithm PSOBSA to address the issues of PSO algorithm, and validates its superior performance through experiments.
ENGINEERING WITH COMPUTERS
(2022)
Article
Chemistry, Multidisciplinary
Mohammad Dehghani, Zeinab Montazeri, Ali Dehghani, Om P. Malik, Ruben Morales-Menendez, Gaurav Dhiman, Nima Nouri, Ali Ehsanifar, Josep M. Guerrero, Ricardo A. Ramirez-Mendoza
Summary: Population-based optimization algorithms, inspired by nature, provide solutions to optimization problems by simulating natural phenomena and physical laws. The Binary Spring Search Algorithm (BSSA) has been validated in various functions, showing competitiveness against high-performance algorithms.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Mohammad H. Nadimi-Shahraki, Shokooh Taghian, Seyedali Mirjalili
Summary: An Improved Grey Wolf Optimizer (I-GWO) is proposed in this article to tackle global optimization and engineering design problems by introducing a dimension learning-based hunting (DLH) search strategy. The IGWO algorithm addresses the lack of population diversity, imbalance between exploitation and exploration, and premature convergence seen in the GWO algorithm. Experimental results show that I-GWO is competitive against six other state-of-the-art metaheuristics, demonstrating its efficiency and applicability in engineering design problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Zeng Meng, Zhuohui Zhang, Gang Li, Dequan Zhang
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2020)
Article
Engineering, Multidisciplinary
Zeng Meng, Zhuohui Zhang, Huanlin Zhou
APPLIED MATHEMATICAL MODELLING
(2020)
Article
Engineering, Multidisciplinary
Zeng Meng, Zhuohui Zhang, Huanlin Zhou, Hanshu Chen, Bo Yu
ENGINEERING OPTIMIZATION
(2020)
Review
Computer Science, Interdisciplinary Applications
Zeng Meng, Gang Li, Xuan Wang, Sadiq M. Sait, Ali Riza Yildiz
Summary: Reliability-based design optimization (RBDO) is an excellent method for balancing economy and safety, but challenges such as global convergence capacity and complex design variables hinder its wider application. This study focuses on applying metaheuristic algorithms to RBDO for improved global convergence, robustness, accuracy, and computational speed, highlighting the differences between metaheuristic and gradient algorithms.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Zeng Meng, Yongsheng Pang, Yuxue Pu, Xuan Wang
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2020)
Article
Engineering, Multidisciplinary
Zeng Meng, Hua-Ping Wan, Zilu Sheng, Gang Li
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2020)
Article
Engineering, Multidisciplinary
Xuan Wang, Kai Long, Zeng Meng, Bo Yu, Changzheng Cheng
Summary: An explicit topology optimization method based on the MMB method is proposed for a multi-material continuum structure with multiple variable-size movable holes. The method utilizes multiple sets of morphable bars and level-set functions to describe the structural topology and geometrical shapes of the holes, projecting them onto density fields to avoid remeshing. The effectiveness of the proposed formulation is demonstrated through numerical examples, showing a reduction in design variables compared to existing optimization frameworks with embedded movable holes.
ENGINEERING OPTIMIZATION
(2021)
Article
Engineering, Multidisciplinary
Zeng Meng, Yang Wu, Xuan Wang, Shanhong Ren, Bo Yu
Summary: This paper presents a hybrid RTO method to address epistemic and aleatory uncertainties in engineering applications, using Monte Carlo simulations and a perturbation method to accelerate convergence. Derivatives of the robust compliance objective function are derived using the adjoint variable method. The proposed method is validated through testing on various beam designs.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Zeng Meng, Shanhong Ren, Xuan Wang, Huanlin Zhou
Summary: The study introduces a novel sequential moving asymptote method (SMAM) to improve the computational efficiency in reliability-based design optimization (RBDO) and avoid finite differences in nested optimization loops. The accuracy and efficiency of SMAM were demonstrated through various mathematical and engineering examples.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Mechanics
Shanhong Ren, Changzheng Cheng, Zeng Meng, Bo Yu, Guozhong Zhao
Summary: This study introduces a new third-order zigzag model for asymmetric and symmetric laminated composite beams. The model accurately describes zigzag effects and provides the results of transverse shear stress field through constitutive equations.
COMPOSITE STRUCTURES
(2021)
Article
Computer Science, Interdisciplinary Applications
Xuan Wang, Hongliang Liu, Zhan Kang, Kai Long, Zeng Meng
Summary: This study tackles the minimum stress design problem in continuum structures with movable holes for the first time, proposing an effective hybrid methodology that optimizes material density and geometric parameters as design variables. By mapping embedded holes to a density field and introducing a new material interpolation scheme, the optimization model successfully minimizes stress in the system.
COMPUTERS & STRUCTURES
(2021)
Article
Computer Science, Interdisciplinary Applications
Zeng Meng, Jingyu Zhao, Chen Jiang
Summary: This paper proposes a semi-analytical extreme value method, which transforms the time-variant performance function into instantaneous performance functions, approximates each instantaneous function by Taylor series expansion at the most probable point through instantaneous reliability analysis, significantly reducing the computational cost of the extreme value method.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Computer Science, Artificial Intelligence
Ran Tao, Zeng Meng, Huanlin Zhou
Summary: The study focuses on the performance of Firefly Algorithm (FA) in engineering design problems and introduces an improved version with self-adaptive strategy (SAFA). By balancing the relationship between exploration and exploitation using self-adaptive strategies, the algorithm's performance is enhanced. When optimizing classical and CEC 2015 benchmark functions, SAFA achieves the best solutions in most cases.
APPLIED SOFT COMPUTING
(2021)
Article
Engineering, Multidisciplinary
Bo Yu, Geyong Cao, Zeng Meng, Yanpeng Gong, Chunying Dong
Summary: In this paper, the isogeometric dual reciprocity boundary element method (IG-DRBEM) is applied to solve 3D transient heat conduction problems in functionally graded materials (FGMs). The theoretical framework of the isogeometric BEM for FGMs problems is established, and the validity of the method is verified through various examples. The effects of different factors on the results are discussed in detail to promote the development of IGBEM.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Engineering, Civil
Zeng Meng, Yongsheng Pang, Huanlin Zhou
Summary: In this study, an augmented weighted simulation method (AWSM) is proposed to tackle the numerical difficulties in reliability analysis of mechanical systems with high-dimensional problems. The basic idea of AWSM is to introduce intermediate events and a space reduction strategy to improve sampling efficiency by converting failure probability to the product of conditional probabilities. The results of mathematical and engineering examples demonstrate the efficiency and accuracy of AWSM for high-dimensional problems.
