1,069 research outputs found

    Performance evaluation of WMN-GA for different mutation and crossover rates considering number of covered users parameter

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    Node placement problems have been long investigated in the optimization field due to numerous applications in location science and classification. Facility location problems are showing their usefulness to communication networks, and more especially from Wireless Mesh Networks (WMNs) field. Recently, such problems are showing their usefulness to communication networks, where facilities could be servers or routers offering connectivity services to clients. In this paper, we deal with the effect of mutation and crossover operators in GA for node placement problem. We evaluate the performance of the proposed system using different selection operators and different distributions of router nodes considering number of covered users parameter. The simulation results show that for Linear and Exponential ranking methods, the system has a good performance for all rates of crossover and mutation.Peer ReviewedPostprint (published version

    A hybrid finite element analysis and evolutionary computation method for the design of lightweight lattice components with optimized strut diameter

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    Components incorporating lattice structures have become very popular lately due to their lightweight nature and the flexibility that additive manufacturing offers with respect to their fabrication. However, design optimization of lattice components has been addressed so far either with empirical approaches or with the use of topology optimization methodologies. An optimization approach utilizing multi-purpose optimization algorithms has not been proposed yet. This paper presents a novel user-friendly method for the design optimization of lattice components towards weight minimization, which combines finite element analysis and evolutionary computation. The proposed method utilizes the cell homogenization technique in order to reduce the computational cost of the finite element analysis and a genetic algorithm in order to search for the most lightweight lattice configuration. A bracket consisting of both solid and lattice regions is used as a case study in order to demonstrate the validity and effectiveness of the method, with the results showing that its weight is reduced by 13.5 % when using lattice structures. A discussion about the efficiency and the implications of the proposed approach is presented

    Structural topology optimization via the genetic algorithm

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    Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1994.Includes bibliographical references (p. 177-186) and index.by Colin Donald Chapman.M.S

    Speciation, clustering and other genetic algorithm improvements for structural topology optimization

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    Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1996.Includes bibliographical references (p. 103-106).by James Wallace Duda.M.S

    Evolutionary Computation

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    This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field

    Advances in Evolutionary Algorithms

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    With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field
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