Genetic Algorithm Approach for Optimization of FRP Laminated Cylindrical Shells Under Constraint

1999 ◽  
Author(s):  
Yoshiki Ohta
Keyword(s):  
Genetic Algorithm ◽  
Cylindrical Shells ◽  
Laminated Composite ◽  
Frequency Equation ◽  
Genetic Operators ◽  
Fundamental Frequencies ◽  
Design Variables ◽  
Structural Applications ◽  
Genetic Algorithm Approach ◽  
Laminated Cylindrical Shells

Abstract Fiber Reinforced Plastic (FRP) materials have been increasingly used in many structural applications of space shuttles, airplanes and automobiles, and the structural optimization of FRP laminated composite shells has been studied for stiffer structural design by many researchers. This paper studies the maximization of fundamental frequencies of FRP laminated cylindrical shells under stiffness constraint by using Genetic Algorithm (GA). For this purpose, the frequency equation for simply-supported shells with symmetrically balanced stacking sequence is derived analytically based on Classical Lamination Theory. In optimization the fiber angles and the thickness ratio of each FRP ply, which have continuous real values, are taken as design variables, and fundamental frequency of the shell is maximized under in-plane stiffness constraints. In numerical experiments, extensive numerical calculations are carried out to determine better genetic operators that would be suitable for FRP laminates design, and genetic parameters are tuned for better reliabilities and lower computational costs in the present GA. Optimal design solutions for various laminated cylindrical shells are obtained and then the applicability of the GA to the maximization of frequencies of the shells is studied from numerical results obtained.

Fiber Orientation Angles Optimization for Maximum Fundamental Frequency of Laminated Composite Plates by the Genetic Algorithm and Meshless Method

2014 ◽  
Vol 709 ◽  
pp. 130-134
Author(s):  
Feng Wang ◽  
Wei Ping Zhao ◽  
Song Xiang
Keyword(s):  
Genetic Algorithm ◽  
Fundamental Frequency ◽  
Fiber Orientation ◽  
Meshless Method ◽  
Laminated Composite ◽  
Composite Plates ◽  
Laminated Plates ◽  
Laminated Composite Plates ◽  
Fundamental Frequencies ◽  
Design Variables

Fiber orientation angles optimization is carried out for maximum fundamental frequency of clamped laminated composite plates using the genetic algorithm. The meshless method is utilized to calculate the fundamental frequency of clamped laminated composite plates. In the present paper, the maximum fundamental frequency is an objective function; design variables are a set of fiber orientation angles in the layers. The examples of square laminated plates are considered. The results for the optimal fiber orientation angles and the maximum fundamental frequencies of the 2-layer plates are presented.

Solving the 0/1 knapsack problem using an adaptive genetic algorithm

2002 ◽  
Vol 16 (1) ◽  
pp. 23-30 ◽  
Author(s):  
ZOHEIR EZZIANE
Keyword(s):  
Genetic Algorithm ◽  
Knapsack Problem ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Adaptive Genetic Algorithm ◽  
Stochastic Algorithms ◽  
Initial Population ◽  
Genetic Operators ◽  
Adaptive Penalty ◽  
Genetic Algorithm Approach

Probabilistic and stochastic algorithms have been used to solve many hard optimization problems since they can provide solutions to problems where often standard algorithms have failed. These algorithms basically search through a space of potential solutions using randomness as a major factor to make decisions. In this research, the knapsack problem (optimization problem) is solved using a genetic algorithm approach. Subsequently, comparisons are made with a greedy method and a heuristic algorithm. The knapsack problem is recognized to be NP-hard. Genetic algorithms are among search procedures based on natural selection and natural genetics. They randomly create an initial population of individuals. Then, they use genetic operators to yield new offspring. In this research, a genetic algorithm is used to solve the 0/1 knapsack problem. Special consideration is given to the penalty function where constant and self-adaptive penalty functions are adopted.

Genetic Algorithm Approach for UAV Persistent Visitation Problem

2018 ◽  
Author(s):  
Alexander L. Von Moll ◽  
David W. Casbeer ◽  
Krishna Kalyanam ◽  
Satyanarayana G. Manyam
Keyword(s):  
Genetic Algorithm ◽  
Computation Time ◽  
Exact Method ◽  
Genetic Operators ◽  
Exact Methods ◽  
Optimal Length ◽  
Algorithm Performance ◽  
Encoding Scheme ◽  
Fixed Length ◽  
Genetic Algorithm Approach

We employ a genetic algorithm approach to solving the persistent visitation problem for UAVs. The objective is to minimize the maximum weighted revisit time over all the sites in a cyclicly repeating walk. In general, the optimal length of the walk is not known, so this method (like the exact methods) assume some fixed length. Exact methods for solving the problem have recently been put forth, however, in the absence of additional heuristics, the exact method scales poorly for problems with more than 10 sites or so. By using a genetic algorithm, performance and computation time can be traded off depending on the application. The main contributions are a novel chromosome encoding scheme and genetic operators for cyclic walks which may visit sites more than once. Examples show that the performance is comparable to exact methods with better scalability.

Planning of Component Placement/Insertion Sequence and Feeder Setup in PCB Assembly Using Genetic Algorithm

1993 ◽  
Vol 115 (4) ◽  
pp. 424-432 ◽  
Author(s):  
M. C. Leu ◽  
H. Wong ◽  
Z. Ji
Keyword(s):  
Genetic Algorithm ◽  
Printed Circuit Board ◽  
Circuit Board ◽  
Assembly Planning ◽  
Genetic Operators ◽  
Printed Circuit Board Assembly ◽  
Component Placement ◽  
Pcb Assembly ◽  
Circuit Board Assembly ◽  
Genetic Algorithm Approach

A new application of the genetic algorithm approach is introduced to solve printed circuit board assembly planning problems. The developed genetic algorithm finds the sequence of component placement/insertion and the arrangement of feeders simultaneously, for achieving the shortest assembly time, for three main types of assembly machines. The algorithm uses links (parents) to represent possible solutions and it applies genetic operators to generate new links (offspring) in an iterative procedure to obtain nearly optimal solutions. Examples are provided to illustrate solutions generated by the algorithm.

Optimization of Joined Conical Shells Based on Free Vibration

2016 ◽  
Author(s):  
Rayehe Karimi Mahabadi ◽  
Firooz Bakhtiari-Nejad
Keyword(s):  
Genetic Algorithm ◽  
Free Vibration ◽  
Natural Frequency ◽  
Conical Shell ◽  
Fibre Orientation ◽  
Laminated Composite ◽  
Conical Shells ◽  
Design Variables

This work aims at utilizing genetic algorithm (GA) to pursue the optimization of joined conical shells based on free vibration. Semi-vertex angles of cones and fibre orientation of the laminated composite are considered as design variables. First, the model is simulated in ABAQUS, the model is validated by comparing its results to other obtained from the literature. Then the first non-zero natural frequency of isotropic joined conical shell is maximized by changing the two semi-vertex angles of cones. Last the fibre orientation of laminated joined shells are optimized to achieve the maximum natural frequency.

Buckling Behavior of Optimal Laminated Composite Cylindrical Shells Subjected to Axial Compression and External Pressure

2011 ◽  
Vol 121-126 ◽  
pp. 48-54 ◽  
Author(s):  
Behzad Abdi ◽  
Hamid Mozafari ◽  
Ayob Amran ◽  
Roya Kohandel ◽  
Ali Alibeigloo
Keyword(s):  
Axial Compression ◽  
Optimization Design ◽  
Cylindrical Shells ◽  
Laminated Composite ◽  
Optimization Procedure ◽  
Imperialist Competitive Algorithm ◽  
External Pressure ◽  
Design Variables ◽  
Buckling Behavior ◽  
Composite Cylindrical Shells

In this study, the buckling behavior of optimum laminated composite cylindrical shells subjected to axial compression and external pressure are studied. The cylindrical shells are composed of multi orthotropic layers that the principal axis gets along with the shell axis (x). The number of layers and the fiber orientation of layers are selected as optimization design variables with the aim to find the optimal laminated composite cylindrical shells. The optimization procedure was formulated with the objective of finding the highest buckling pressure. The Genetic Algorithm (GA) and Imperialist Competitive Algorithm (ICA) are two optimization algorithms that are used in this optimization procedure and the results were compared. Also, the effect of materials properties on buckling behavior was analyzed and studied.

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