966 research outputs found

    Dynamic Water Strider Algorithm for Optimal Design of Skeletal Structures

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    In the present paper, a dynamic version of Water Strider Algorithm (WSA) is proposed. The WSA as well as the Dynamic Water Strider Algorithm (DWSA) are applied to minimize the weight of several skeletal structures. WSA is a nature-inspired metaheuristic that mimics the territorial behavior, intelligent ripple communication, mating style, feeding mechanisms, and succession of water strider insects. The efficiency of these algorithms is tested by optimizing different truss and frame structures subject to multiple loading conditions and constraints. Comparing the results obtained by DWSA with those of other methods it becomes evident that DWSA is a suitable technique for optimizing the structural design and minimizing the weight of structures while fulfilling all constraints

    Performance assessment of meta-heuristics for composite layup optimisation

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    Otimização estrutural de pórticos espaciais de aço via algoritmos de evolução diferencial

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    Spatial steel frames are structural systems widely applied in the most diverse branches of civil engineering. Common applications of this type of structure are found in residential and commercial buildings, industrial sheds, warehouses, airports, hospitals, cultural centers such as museums, sports stadiums, among others. In taller buildings, factors such as horizontal displacements due to wind loads, natural frequencies of vibration, and global stability become more relevant. With the advancement of engineering, the need for increasingly competitive and optimized projects emerged, arousing the search for computational methodologies capable of solving such problems. In the last decades, meta-heuristics have proven increasing efficiency and robustness in solving problems of this nature. This dissertation makes a study of structural optimization via differential evolution algorithms applied to spatial steel frames, having as an innovative point the addition of constraints related to the dynamic behavior and the global stability of the structure, in general neglected. Three sets of experiments are conducted, in which analyses of braced and unbraced structural systems, as well as studies for cardinality constraints and automatic member grouping, are taken into account in the steel frames optimization problems.Os pórticos espaciais de aço são sistemas estruturais vastamente aplicados nos mais diversos ramos da engenharia civil. Aplicações comuns desse tipo de estrutura são encontradas em prédios residenciais ou comerciais, galpões industriais, almoxarifados, aeroportos, hospitais, centros culturais como museus, estádios desportivos, entre outros. À medida que as construções vão se tornando cada vez mais altas, fatores como deslocamentos horizontais devido às cargas de vento, frequências naturais de vibração e estabilidade global da estrutura passam a ser mais relevantes em relação as restrições de resistência. Com o avanço da engenharia, veio a necessidade de projetos cada vez mais competitivos e otimizados, despertando a procura de metodologias computacionais capazes de resolver tais problemas. Nas últimas décadas as meta-heurísticas vieram mostrando eficiência e robustez crescentes na solução de problemas dessa natureza. Esta dissertação faz um estudo de otimização estrutural via algoritmos de evolução diferencial aplicado aos pórticos espaciais de aço, tendo como caráter inovador a adição de restrições relativas ao comportamento dinâmico e à estabilidade global da estrutura, em geral negligenciadas. Três conjuntos de experimentos são conduzidos, nos quais análises de sistemas estruturais contraventados e não-contraventados, bem como estudos para restrição de cardinalidade e agrupamento automático de membros são levados em consideração na otimização das estruturas de aço.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superio

    A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

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    Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

    Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

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    The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications

    Inverse Kinematic Analysis of Robot Manipulators

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    An important part of industrial robot manipulators is to achieve desired position and orientation of end effector or tool so as to complete the pre-specified task. To achieve the above stated goal one should have the sound knowledge of inverse kinematic problem. The problem of getting inverse kinematic solution has been on the outline of various researchers and is deliberated as thorough researched and mature problem. There are many fields of applications of robot manipulators to execute the given tasks such as material handling, pick-n-place, planetary and undersea explorations, space manipulation, and hazardous field etc. Moreover, medical field robotics catches applications in rehabilitation and surgery that involve kinematic, dynamic and control operations. Therefore, industrial robot manipulators are required to have proper knowledge of its joint variables as well as understanding of kinematic parameters. The motion of the end effector or manipulator is controlled by their joint actuator and this produces the required motion in each joints. Therefore, the controller should always supply an accurate value of joint variables analogous to the end effector position. Even though industrial robots are in the advanced stage, some of the basic problems in kinematics are still unsolved and constitute an active focus for research. Among these unsolved problems, the direct kinematics problem for parallel mechanism and inverse kinematics for serial chains constitute a decent share of research domain. The forward kinematics of robot manipulator is simpler problem and it has unique or closed form solution. The forward kinematics can be given by the conversion of joint space to Cartesian space of the manipulator. On the other hand inverse kinematics can be determined by the conversion of Cartesian space to joint space. The inverse kinematic of the robot manipulator does not provide the closed form solution. Hence, industrial manipulator can achieve a desired task or end effector position in more than one configuration. Therefore, to achieve exact solution of the joint variables has been the main concern to the researchers. A brief introduction of industrial robot manipulators, evolution and classification is presented. The basic configurations of robot manipulator are demonstrated and their benefits and drawbacks are deliberated along with the applications. The difficulties to solve forward and inverse kinematics of robot manipulator are discussed and solution of inverse kinematic is introduced through conventional methods. In order to accomplish the desired objective of the work and attain the solution of inverse kinematic problem an efficient study of the existing tools and techniques has been done. A review of literature survey and various tools used to solve inverse kinematic problem on different aspects is discussed. The various approaches of inverse kinematic solution is categorized in four sections namely structural analysis of mechanism, conventional approaches, intelligence or soft computing approaches and optimization based approaches. A portion of important and more significant literatures are thoroughly discussed and brief investigation is made on conclusions and gaps with respect to the inverse kinematic solution of industrial robot manipulators. Based on the survey of tools and techniques used for the kinematic analysis the broad objective of the present research work is presented as; to carry out the kinematic analyses of different configurations of industrial robot manipulators. The mathematical modelling of selected robot manipulator using existing tools and techniques has to be made for the comparative study of proposed method. On the other hand, development of new algorithm and their mathematical modelling for the solution of inverse kinematic problem has to be made for the analysis of quality and efficiency of the obtained solutions. Therefore, the study of appropriate tools and techniques used for the solution of inverse kinematic problems and comparison with proposed method is considered. Moreover, recommendation of the appropriate method for the solution of inverse kinematic problem is presented in the work. Apart from the forward kinematic analysis, the inverse kinematic analysis is quite complex, due to its non-linear formulations and having multiple solutions. There is no unique solution for the inverse kinematics thus necessitating application of appropriate predictive models from the soft computing domain. Artificial neural network (ANN) can be gainfully used to yield the desired results. Therefore, in the present work several models of artificial neural network (ANN) are used for the solution of the inverse kinematic problem. This model of ANN does not rely on higher mathematical formulations and are adept to solve NP-hard, non-linear and higher degree of polynomial equations. Although intelligent approaches are not new in this field but some selected models of ANN and their hybridization has been presented for the comparative evaluation of inverse kinematic. The hybridization scheme of ANN and an investigation has been made on accuracies of adopted algorithms. On the other hand, any Optimization algorithms which are capable of solving various multimodal functions can be implemented to solve the inverse kinematic problem. To overcome the problem of conventional tool and intelligent based method the optimization based approach can be implemented. In general, the optimization based approaches are more stable and often converge to the global solution. The major problem of ANN based approaches are its slow convergence and often stuck in local optimum point. Therefore, in present work different optimization based approaches are considered. The formulation of the objective function and associated constrained are discussed thoroughly. The comparison of all adopted algorithms on the basis of number of solutions, mathematical operations and computational time has been presented. The thesis concludes the summary with contributions and scope of the future research work

    Pertanika Journal of Science & Technology

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    Pertanika Journal of Science & Technology

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    Course Description

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