scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Optimal design of a composite leaf spring using genetic algorithms

01 Apr 2001-Computers & Structures (Pergamon)-Vol. 79, Iss: 11, pp 1121-1129
TL;DR: In this article, a formulation and solution technique using genetic algorithms (GA) for design optimization of composite leaf springs is presented, where the optimum dimensions of a composite leaf spring have been obtained, which contributes towards achieving the minimum weight with adequate strength and stiffness.
About: This article is published in Computers & Structures.The article was published on 2001-04-01. It has received 138 citations till now. The article focuses on the topics: Leaf spring & Unsprung mass.
Citations
More filters
Journal ArticleDOI
TL;DR: In this paper, the main optimization methods for composite laminate with uniform stacking sequence through their entire structure are described, their characteristic features are contrasted, and the potential areas requiring more investigation are highlighted.

291 citations

Journal ArticleDOI
01 Jan 2011
TL;DR: The performance of ABC is at par with that of PSO, AIS and GA for all the loading configurations and is evaluated in comparison with other nature inspired techniques which includes Particle Swarm Optimization (PSO), Artificial Immune System (AIS) and Genetic Algorithm (GA).
Abstract: In this paper, we present a generic method/model for multi-objective design optimization of laminated composite components, based on Vector Evaluated Artificial Bee Colony (VEABC) algorithm VEABC is a parallel vector evaluated type, swarm intelligence multi-objective variant of the Artificial Bee Colony algorithm (ABC) In the current work a modified version of VEABC algorithm for discrete variables has been developed and implemented successfully for the multi-objective design optimization of composites The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength The primary optimization variables are the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria: failure mechanism based failure criteria, maximum stress failure criteria and the tsai-wu failure criteria The optimization method is validated for a number of different loading configurations-uniaxial, biaxial and bending loads The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented Finally the performance is evaluated in comparison with other nature inspired techniques which includes Particle Swarm Optimization (PSO), Artificial Immune System (AIS) and Genetic Algorithm (GA) The performance of ABC is at par with that of PSO, AIS and GA for all the loading configurations

275 citations

Journal ArticleDOI
TL;DR: Genetic algorithms (GAs) are biologically inspired computing techniques, which tend to mimic the basic Darwinian concepts of natural selection, and are highly robust and efficient for most engineering optimising studies as mentioned in this paper.
Abstract: Genetic algorithms (GAs) are biologically inspired computing techniques, which tend to mimic the basic Darwinian concepts of natural selection. They are highly robust and efficient for most engineering optimising studies. Although a late entrant in the materials arena, GAs based studies are increasingly making their presence felt in many different aspects of this discipline. In recent times, GAs have been successfully used in numerous problems in the areas of atomistic material design, alloy design, polymer processing, powder compaction and sintering, ferrous production metallurgy, continuous casting, metal rolling, metal cutting, welding, and so on. The present review attempts to present the state of the art in this area. It includes three broad sections given as: fundamentals of genetic algorithms, genetic algorithms in materials design, and genetic algorithms in materials processing. The first section provides the reader with the basic concepts and the intricacies associated with this novel tec...

182 citations

Journal ArticleDOI
TL;DR: A genetic algorithm based approach is developed to optimise fixture layout through integrating a finite element code running in batch mode to compute the objective function values for each generation.

173 citations

Journal ArticleDOI
TL;DR: A new, generic method/model for multi-objective design optimization of laminated composite components using a novel multi- objective optimization algorithm developed on the basis of the Quantum behaved Particle Swarm Optimization (QPSO) paradigm is presented.
Abstract: We present a new, generic method/model for multi-objective design optimization of laminated composite components using a novel multi-objective optimization algorithm developed on the basis of the Quantum behaved Particle Swarm Optimization (QPSO) paradigm. QPSO is a co-variant of the popular Particle Swarm Optimization (PSO) and has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; Failure Mechanism based Failure criteria, Maximum stress failure criteria and the Tsai-Wu Failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences as well as fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. Also, the performance of QPSO is compared with the conventional PSO.

172 citations

References
More filters
Book
01 Sep 1988
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Abstract: From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs No prior knowledge of GAs or genetics is assumed, and only a minimum of computer programming and mathematics background is required

52,797 citations

01 Jan 1989
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Abstract: From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields. Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs. No prior knowledge of GAs or genetics is assumed, and only a minimum of computer programming and mathematics background is required.

33,034 citations

Journal ArticleDOI
TL;DR: A penalty‐based transformation method depends on the degree of constraint violation, which is found to be wellsuited for a parallel search using genetic algorithms.
Abstract: Optimizing most structural systems used in practice requires considering design variables as discrete quantities. The paper presents a simple genetic algorithm for optimizing structural systems with discrete design variables. As genetic algorithms (GAs) are best suited for unconstrained optimization problems, it is necessary to transform the constrained problem into an unconstrained one. A penalty‐based transformation method is used in the present work. The penalty parameter depends on the degree of constraint violation, which is found to be wellsuited for a parallel search using genetic algorithms. The concept of optimization using the genetic algorithm is presented in detail using a three‐bar truss problem. All the computations for three successive generations are presented in the form of tables for easy understanding of the algorithm. Two standard problems from literature are solved and results compared. The application of the genetic algorithm to design optimization of a larger problem is illustrated ...

784 citations

Journal ArticleDOI
TL;DR: In this article, the use of a genetic algorithm for the minimum thickness design of composite laminated plates is explored, by incorporating knowledge of the physics of the problem into the genetic algorithm.

201 citations

Dissertation
01 Jan 1988
TL;DR: In this article, the dimensions of the double-tapered FRP leaf spring were investigated and the optimal taper ratio was proved to be 0·5, and a new device for attachment of the longitudinal type double tapered leaf spring to the vehicle was prepared.
Abstract: Abstract Fundamental properties of the dimensioning of the double tapered FRP leaf spring were investigated. The optimal taper ratio was proved to be 0·5. Prototype longitudinal type double tapered leaf springs to replace four leaf steel springs were made from glass fibre and epoxy. A new device for attachment of the longitudinal type double tapered GRP leaf spring to the vehicle was prepared. Prototype GRP leaf springs showed a superior endurance and fail-safe characteristics, and the device for vehicle attachment was proved to have a sufficient strength.

66 citations