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  • Open Access


    Enhanced Harris Hawks Optimization Integrated with Coot Bird Optimization for Solving Continuous Numerical Optimization Problems

    Hao Cui, Yanling Guo*, Yaning Xiao, Yangwei Wang*, Jian Li, Yapeng Zhang, Haoyu Zhang

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1635-1675, 2023, DOI:10.32604/cmes.2023.026019

    Abstract Harris Hawks Optimization (HHO) is a novel meta-heuristic algorithm that imitates the predation characteristics of Harris Hawk and combines Lévy flight to solve complex multidimensional problems. Nevertheless, the basic HHO algorithm still has certain limitations, including the tendency to fall into the local optima and poor convergence accuracy. Coot Bird Optimization (CBO) is another new swarm-based optimization algorithm. CBO originates from the regular and irregular motion of a bird called Coot on the water’s surface. Although the framework of CBO is slightly complicated, it has outstanding exploration potential and excellent capability to avoid falling into local optimal solutions. This paper… More > Graphic Abstract

    Enhanced Harris Hawks Optimization Integrated with Coot Bird Optimization for Solving Continuous Numerical Optimization Problems

  • Open Access


    Technique for Multi-Pass Turning Optimization Based on Gaussian Quantum-Behaved Bat Algorithm

    Shutong Xie, Zongbao He, Xingwang Huang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1575-1602, 2023, DOI:10.32604/cmes.2023.025812

    Abstract The multi-pass turning operation is one of the most commonly used machining methods in manufacturing field. The main objective of this operation is to minimize the unit production cost. This paper proposes a Gaussian quantum-behaved bat algorithm (GQBA) to solve the problem of multi-pass turning operation. The proposed algorithm mainly includes the following two improvements. The first improvement is to incorporate the current optimal positions of quantum bats and the global best position into the stochastic attractor to facilitate population diversification. The second improvement is to use a Gaussian distribution instead of the uniform distribution to update the positions of… More >

  • Open Access


    A Novel Hybrid Tunicate Swarm Naked Mole-Rat Algorithm for Image Segmentation and Numerical Optimization

    Supreet Singh1,2, Nitin Mittal1, Urvinder Singh2, Rohit Salgotra2, Atef Zaguia3, Dilbag Singh4,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3445-3462, 2022, DOI:10.32604/cmc.2022.023004

    Abstract This paper provides a new optimization algorithm named as tunicate swarm naked mole-rat algorithm (TSNMRA) which uses hybridization concept of tunicate swarm algorithm (TSA) and naked mole-rat algorithm (NMRA). This newly developed algorithm uses the characteristics of both algorithms (TSA and NMRA) and enhance the exploration abilities of NMRA. Apart from the hybridization concept, important parameter of NMRA such as mating factor is made to be self-adaptive with the help of simulated annealing mutation operator and there is no need to define its value manually. For evaluating the working capabilities of proposed TSNMRA, it is tested for 100-digit challenge (CEC… More >

  • Open Access


    New Modified Controlled Bat Algorithm for Numerical Optimization Problem

    Waqas Haider Bangyal1, Abdul Hameed1, Jamil Ahmad2, Kashif Nisar3,*, Muhammad Reazul Haque4, Ag. Asri Ag. Ibrahim3, Joel J. P. C. Rodrigues5,6, M. Adil Khan7, Danda B. Rawat8, Richard Etengu4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2241-2259, 2022, DOI:10.32604/cmc.2022.017789

    Abstract Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats’ searching behavior. BA faces premature convergence due to its local search capability. Instead of using the standard uniform walk, the Torus walk is viewed as a promising alternative to improve the local search capability. In this work, we proposed an improved variation of BA by applying torus walk to improve diversity and convergence. The proposed. Modern Computerized Bat Algorithm (MCBA) approach has been examined for fifteen well-known benchmark… More >

  • Open Access


    Numerical Optimization Algorithm for Unsteady Flows of Rotor Based on Web Service

    Jilin Zhang1,4,5, Xuechao Liu1,5, Jian Wan2,1,5, Yongjian Ren1,5, Binglin Xu1,5, Jianfan He1,5, Yuchen Fan1,5, Li Zhou1,5, Zhenguo Wei6, Juncong Zhang6, Jue Wang3

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 527-546, 2019, DOI:10.31209/2019.100000109

    Abstract A numerical optimization algorithm for unsteady flows of rotor based on web service is proposed. Space discretization uses the finite volume method, time discretization uses the implicit dual-time steps method, and turbulence model uses the Spalart–Allmaras (S–A) model. In order to efficiently use the computing resources of the cluster, a service-oriented service computing architecture is used in a parallel computing service program. In order to realize the load balance of hybrid grid partition, the grid is partitioned by Metis Library. Meanwhile, data communication based on Message Passing Interface (MPI) technology guarantees the consistency of convergence between parallel algorithm and serial… More >

  • Open Access


    An Enhanced Formulation of the Maximum Entropy Method for Structural Optimization

    S. Hernández1,2, A. Baldomir1, J. Díaz1, F. Pereira1

    CMC-Computers, Materials & Continua, Vol.32, No.3, pp. 219-240, 2012, DOI:10.3970/cmc.2012.032.219

    Abstract A numerical optimization method was proposed time ago by Templeman based on the maximum entropy principle. That approach combined the Kuhn-Tucker condition and the information theory postulates to create a probabilistic formulation of the optimality criteria techniques. Such approach has been enhanced in this research organizing the mathematical process in a single optimization loop and linearizing the constraints. It turns out that such procedure transforms the optimization process in a sequence of systems of linear equations which is a very efficient way of obtaining the optimum solution of the problem. Some examples of structural optimization, namely, a planar truss, a… More >

  • Open Access


    Weighted Sparse Image Classification Based on Low Rank Representation

    Qidi Wu1, Yibing Li1, Yun Lin1,*, Ruolin Zhou2

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 91-105, 2018, DOI: 10.3970/cmc.2018.02771

    Abstract The conventional sparse representation-based image classification usually codes the samples independently, which will ignore the correlation information existed in the data. Hence, if we can explore the correlation information hidden in the data, the classification result will be improved significantly. To this end, in this paper, a novel weighted supervised spare coding method is proposed to address the image classification problem. The proposed method firstly explores the structural information sufficiently hidden in the data based on the low rank representation. And then, it introduced the extracted structural information to a novel weighted sparse representation model to code the samples in… More >

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