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A Review of Nature-Inspired algorithms

JOURNAL OF BIONIC ENGINEERING 2010年第4期7卷 S232-S237页

作者： Zang, Hongnian Zhang, Shujun Hapeshi, Kevin Univ Gloucestershire Dept Comp Cheltenham GL50 2RH Glos England

The study of bionics bridges the functions, biological structures and organizational principles found in nature with our modern technologies, and numerous mathematical and metaheuristic algorithms have been developed along with the knowledge transferring process from the lifeforms to the human technologies. Output of bionics study includes not only physical products, but also various computation methods that can be applied in different areas. People have learnt from biological systems and structures to design and develop a number of different kinds of optimisation algorithms that have been widely used in both theoretical study and practical applications. In this paper, a number of selected nature-inspired algorithms are systematically reviewed and analyzed. Though the paper is mainly focused on the original principle behind each of the algorithm, their applications are also discussed.

关键词： bionic optimization algorithms review Ant Colony Optimization bees algorithm Genetic algorithm Firefly algorithm

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Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony algorithm Based on Opposition-Based Learning

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INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION 2016年第4-18期2016卷 2749035-2749035页

作者： Yang, Chao Zhang, Jian-Ke Guo, Li-Xin Xian Univ Posts & Telecommun Sch Sci Xian 710121 Peoples R China Xidian Univ Sch Phys & Optoelect Engn Xian 710071 Peoples R China

The artificial bee colony (ABC) algorithm is a recently introduced optimization method in the research field of swarm intelligence. This paper presents an improved ABC algorithm named as OGABC based on opposition-based learning (OBL) and global best search equation to overcome the shortcomings of the slow convergence rate and sinking into local optima in the process of inversion of atmospheric duct. Taking the inversion of the surface duct using refractivity from clutter (RFC) technique as an example to validate the performance of the proposed OGABC, the inversion results are compared with those of the modified invasive weed optimization (MIWO) and ABC. The radar sea clutter power calculated by parabolic equation method using the simulated and measured refractivity profile is utilized to carry out the inversion of the surface duct, respectively. The comparative investigation results indicate that the performance of OGABC is superior to that of MIWO and ABC in terms of stability, accuracy, and convergence rate during the process of inversion.

关键词： Atmospheric electromagnetic wave propagation bees algorithm Swarm intelligence Clutter (Radar) Mathematical optimization

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Human-robot collaborative disassembly line balancing considering the safe strategy in remanufacturing

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JOURNAL OF CLEANER PRODUCTION 2021年 324卷 129158-129158页

作者： Xu, Wenjun Cui, Jia Liu, Bin Liu, Jiayi Yao, Bitao Zhou, Zude Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Peoples R China Wuhan Univ Technol Hubei Key Lab Broadband Wireless Commun & Sensor Wuhan 430070 Peoples R China Wuhan Univ Technol Sch Mech & Elect Engn Wuhan 430070 Peoples R China

Remanufacturing is an important method to realize resource saving and circular economy. Disassembly is a vital step of remanufacturing and it is always finished by manual labor which is low efficiency. Although robotic disassembly covers the shortages of manual disassembly, it is still difficult for the robots to independently finish the disassembly process without the operator's assistance. The human-robot collaborative disassembly is being paid increasing attention and the human-robot collaborative disassembly line balancing is to assign suitable disassembly tasks to each human-robot collaborative disassembly workstation in a balanced manner. In humanrobot collaborative disassembly, the operator's safety should be considered when the robot collaboratively executes the disassembly tasks with the operator. In this paper, disassembly information model of human-robot collaborative disassembly considering the safe strategy is studied. After that, this paper solves the humanrobot collaborative disassembly line balancing problem using the improved discrete bees algorithm. To verify the proposed method, case study based on a bearing coupler is carried out. The results show the proposed improved discrete bees algorithm can generate the optimal solutions of human-robot collaborative disassembly line balancing problem considering the safe strategy and finds better solutions compared with the other optimization algorithms in terms of running time, average generational distance and Pareto fronts.

关键词： Human-robot collaborative disassembly Disassembly line balancing problem Remanufacturing Safe strategy bees algorithm

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Training Spiking Neural Models Using Artificial Bee Colony

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2015年第1期2015卷 14-14页

作者： Vazquez, Roberto A. Garro, Beatriz A. La Salle Univ Fac Engn Intelligent Syst Grp Mexico City 06140 DF Mexico Univ Nacl Autonoma Mexico Inst Invest Matemat Aplicadas & Sistemas Mexico City 04510 DF Mexico

Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy.

关键词： bees algorithm PATTERN recognition systems NEURON analysis PROBLEM solving NEURAL networks (Computer science) PERFORMANCE evaluation

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Nonlinear vibration and geometric optimization of nanocomposite multilayer organic solar cell under wind loading

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THIN-WALLED STRUCTURES 2021年 158卷 107199-107199页

作者： Vu Minh Anh Tran Quoc Quan Phuong Tran Phenikaa Univ Phenikaa Inst Adv Study PIAS Hanoi 12116 Vietnam Univ Engn & Technol VNU Hanoi Dept Engn & Technol Construct & Transportat 144 Xuan Thuy Hanoi Vietnam RMIT Univ Dept Civil & Infrastruct Engn Melbourne Vic Australia

This paper presents an analytical approach on the nonlinear vibration of nanocomposite multilayer organic solar cell (NMOSC) subjected to the combination of wind load and uniform temperature change. The NMOSC comprises of five layers, which are made of Al, P3HT:PCBM, PEDOT:PSS, Graphene and Glass. Compared to common models of the NMOSC, ITO is replaced by graphene to control the output colors of NMOSC. The nonlinear motion equations and the compatibility equation are deriving by taking into account the effect of viscous damping, von Karman nonlinearity terms, elastic foundations and initial imperfection. The formula of the wind load is improved for consideration in the general case that the direction of the wind load is not just perpendicular to the structure. Four edges of the NMOSC are assumed to be simply supported and immovable in the transverse plane. The Galerkin and Runge - Kutta methods are applied to obtain the dynamic response and the natural frequency of the NMOSC. Four optimization algorithms (bees algorithm, Basic differential evolution algorithm, enhanced colliding bodies optimization algorithm, social group optimization algorithm) are used to determine the maximum value of natural frequency of the NMOCS, which depends on nine variables including the geometrical parameters, elastic foundations stiffness and temperature increment. In the numerical results, the effects of elastic foundations, initial imperfection, viscous damping ratio, temperature increment, wind load and the length to width ratio on the dynamic response and natural frequency are considered in details. The maximum values of the natural frequency of the NMOSC with four algorithms are obtained and compared. The results show that the optimal value obtained by four algorithms is close to each other. However, the calculation time with enhanced colliding bodies optimization algorithm is the fastest and with bees algorithm is the longest of all.

关键词： Organic solar cell Nonlinear vibration Geometric optimization Wind load bees algorithm

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Static buckling analysis and geometrical optimization of magneto-electro-elastic sandwich plate with auxetic honeycomb core

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THIN-WALLED STRUCTURES 2022年 173卷 108935-108935页

作者： Vu Dinh Quang Tran Quoc Quan Tran, Phuong Phenikaa Univ Phenikaa Inst Adv Study PIAS Hanoi 12116 Vietnam Phenikaa Univ Fac Mech Engn & Mechatron Hanoi 12116 Vietnam RMIT Univ Sch Engn Melbourne Vic Australia

The nonlinear static buckling analysis of magneto-electro-elastic sandwich plate on Pasternak-type elastic foundations subjected to the mechanical, thermal, electric and magnetic loadings is presented in this paper. The sandwich plate is composed of an auxetic honeycomb core with negative Poisson's ratio and two face sheets made of magneto-electro-elastic material. The system basic equations are derived based on the Reddy's higher order shear deformation plate theory taking into account the effect of von Karman the kinematic nonlinearity and initial imperfection. The form of possible solutions and electric, magnetic potentials are chosen as trigonometric functions based on two cases of boundary conditions. The relationship between axial compressive loading and dimensionless deflection amplitude is determined by using the Galerkin method. For optimization problem, the bees algorithm is applied to obtain the maximum value of critical buckling load of the sandwich plate which depends on five geometrical and material parameters. The effects of elastic foundations, temperature increment, geometrical parameters and electric and magnetic potentials on the stability characteristics are investigated in numerical results. The accuracy and reliability of present approach is confirmed by comparisons with the existing results in the literature.

关键词： Nonlinear static buckling Geometrical optimization Magneto-electro-elastic sandwich plate Auxetic honeycomb core bees algorithm

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Multi-objective grasp pose optimisation for robotic 3D pipe assembly manipulation

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2022年第0期76卷 102326-102326页

作者： Zhang, Zebang Saadat, Mozafar Univ Birmingham Sch Engn Dept Mech Engn Birmingham B15 2TT W Midlands England

This paper considers the problem of grasp pose optimisation for manipulating 3D pipe assemblies during the manufacturing process. The method presented in this paper is specifically developed for manufacturing cryogenic pipe assemblies autonomously in a Factory-In-A-Box scenario (i.e., a compact factory built inside an industrial container). However, it also can be used for robotic manipulation of general frame structures. The problem is formulated as a constrained multi-objective optimisation problem. The optimisation algorithm searches for solutions that satisfy two constraints: (i) robot workspace reachability (i.e., feasible inverse kinematics solution for a given end-effector pose);and (ii) any possible collision when executing the post-grasp trajectory, and continuously improves them based on three objectives: (i) minimise robot joint motion for executing a specified pipe trajectory;(ii) minimise the sum of maximum deformation of pipe assembly along the trajectory;and (iii) minimise the sum of robot force manipulability along the trajectory. A special constraint handling method is used to decouple the constraint and objective evaluation process, allowing expensive objectives to be evaluated only when constraints are satisfied. The algorithm explicitly considers the possibility of multiple inverse kinematics solutions and uses a graph search algorithm (Dijkstra's algorithm) to find the optimal trajectory amongst all feasible trajectories. The weighted sum approach is used to combine the three objectives with weights determined by the Analytical Hierarchy Process. The optimisation problem is solved using the bees algorithm with a proposed problem-specific local search strategy. Extensive benchmarks show that the proposed strategy achieves better overall results than the default strategy of the bees algorithm and other metaheuristics.

关键词： 3D pipe assembly Multi-objective optimization Grasp pose optimization Robotic manipulation Deformable object bees algorithm

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Nonlinear thermal dynamic buckling and global optimization of smart sandwich plate with porous homogeneous core and carbon nanotube reinforced nanocomposite layers

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EUROPEAN JOURNAL OF MECHANICS A-SOLIDS 2021年 90卷 104351-104351页

作者： Dat, Ngo Dinh Quan, Tran Quoc Duc, Nguyen Dinh Phenikaa Univ Phenikaa Inst Adv Study PIAS Hanoi 12116 Vietnam Phenikaa Univ Fac Mech Engn & Mechatron Hanoi 12116 Vietnam Univ Engn & Technol Dept Engn & Technol Construct & Transportat VNU Hanoi 144 Xuan Thuy Hanoi Vietnam

The analytical investigation for the nonlinear thermal dynamic buckling of smart sandwich plate subjected to mechanical, thermal and electric loadings is presented. The sandwich plate is composed of a porous homogeneous core, two carbon nanotube reinforced composite (CNTRC) layers and two piezoelectric face sheets. Basic equations are derived based on the Reddy's higher order shear deformation plate theory and Hamilton's principle in which the initial imperfection and Pasternak-type elastic foundations are included. The external pressure is assumed to be uniformly distributed on the surface of the sandwich plate and depend on time according to the linear functions. The nonlinear dynamic response, the frequency - amplitude relation are obtained by using the Galerkin and Runge - Kutta methods and the critical dynamic buckling load is determined by using Budiansky - Roth criterion. bees algorithm is used to determine the maximum value of natural frequency of smart sandwich plate and the corresponding optimum values of geometrical and material parameters. The effects of geometrical parameters, CNT volume fraction, elastic foundations, temperature increment, initial imperfection and porosity coefficient on the nonlinear vibration and dynamic buckling of the smart sandwich plate are considered specifically. The numerical results are also compared with existing results using different theories.

关键词： Nonlinear thermal dynamic buckling Global optimization Smart sandwich plate Carbon nanotube reinforced nanocomposite bees algorithm

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Hierarchical Artificial Bee Colony Optimizer with Divide-and-Conquer and Crossover for Multilevel Threshold Image Segmentation

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DISCRETE DYNAMICS IN NATURE AND SOCIETY 2014年第1期2014卷 1-22页

作者： He, Maowei Hu, Kunyuan Zhu, Yunlong Ma, Lianbo Chen, Hanning Song, Yan Chinese Acad Sci Shenyang Inst Automat Dept Informat Serv & Intelligent Control Shenyang 110016 Peoples R China Univ Chinese Acad Sci Beijing 100039 Peoples R China

This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization (HABC), for multilevel threshold image segmentation, which employs a pool of optimal foraging strategies to extend the classical artificial bee colony framework to a cooperative and hierarchical fashion. In the proposed hierarchical model, the higher-level species incorporates the enhanced information exchange mechanism based on crossover operator to enhance the global search ability between species. In the bottom level, with the divide-and-conquer approach, each subpopulation runs the original ABC method in parallel to part-dimensional optimum, which can be aggregated into a complete solution for the upper level. The experimental results for comparing HABC with several successful EA and SI algorithms on a set of benchmarks demonstrated the effectiveness of the proposed algorithm. Furthermore, we applied the HABC to the multilevel image segmentation problem. Experimental results of the new algorithm on a variety of images demonstrated the performance superiority of the proposed algorithm.

关键词： bees algorithm MULTILEVEL models (Statistics) SEGMENTATION (Image processing) THRESHOLDING algorithms INFORMATION sharing

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Multiple Input Delays Estimation Using an Artificial Bee Colony algorithm

ABSTRACT AND APPLIED ANALYSIS

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ABSTRACT AND APPLIED ANALYSIS 2013年第Spe12期2013卷 1-6页

作者： Chang, Wei-Der Shu Te Univ Dept Comp & Commun Kaohsiung 824 Taiwan

This paper focuses on the time delay estimation of the system described in the form of discrete-time state equation with multiple input delays. To estimate the input delays, a new evolutionary computation called the artificial bee colony (ABC) algorithm is utilized. This algorithm is originally motivated from the social behaviors of honeybee organization, and it has been proven to be a powerful means for solving the optimized problem. Based on the proposed algorithm, the unknown system input delays can be further solved by minimizing a quadratic cost function of the system. Two illustrative examples are provided to verify the potential of the presented method in the time delay estimation. Some simulations containing different initial condition examinations and appearance of noises are further given. Numerical results show that the proposed method can do well in the multiple inputs delay estimation of discrete-time state equations.

关键词： TIME delay systems bees algorithm ESTIMATION theory DISCRETE-time systems PROBLEM solving NUMERICAL analysis

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