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

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 >

Supreet Singh^1,2, Nitin Mittal¹, Urvinder Singh², Rohit Salgotra², Atef Zaguia³, Dilbag Singh^4,*

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 >

Waqas Haider Bangyal¹, Abdul Hameed¹, Jamil Ahmad², Kashif Nisar^3,*, Muhammad Reazul Haque⁴, Ag. Asri Ag. Ibrahim³, Joel J. P. C. Rodrigues^5,6, 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 >

Jilin Zhang^1,4,5, Xuechao Liu^1,5, Jian Wan^2,1,5, Yongjian Ren^1,5, Binglin Xu^1,5, Jianfan He^1,5, Yuchen Fan^1,5, Li Zhou^1,5, 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 >

S. Hernández^1,2, 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 >

Qidi Wu¹, Yibing Li¹, Yun Lin^1,*, 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 >