Understanding Genetic Algorithm (GA) Operators Step by Step

2021 ◽  
pp. 100-114
Keyword(s):  
Genetic Algorithm ◽  
Soft Computing ◽  
Science And Technology ◽  
Soft Computing Techniques ◽  
Question And Answer ◽  
Traditional Approaches ◽  
Answer Format

In today's world of soft computing, GAs are a hot topic. Researchers developed this fascinating application to face or to counter many difficult problems which cannot be solved through traditional approaches. We have seen that in the published work of GAs, an author does not reveal the working of the GA as a whole. In this chapter, the authors tried to untwist the GA methodology. This knowledge will be helpful in applying GAs for various applications (i.e., in the fields of science and technology and business). In the case of business-related problems, the use of GAs will have viable value. This chapter is a guide to using GAs vs. other soft computing techniques. Later in the chapter, the authors explain the working and comparison of GAs by using question and answer format.

scholarly journals Automatic Procedures as Help for Optimal Cam Design

2006 ◽  
Author(s):  
Massimo Antonini ◽  
Alberto Borboni ◽  
Roberto Bussola ◽  
Rodolfo Faglia
Keyword(s):  
Genetic Algorithm ◽  
Soft Computing ◽  
Design Process ◽  
Model Identification ◽  
Optimization Method ◽  
Realistic Model ◽  
Design Problems ◽  
Soft Computing Techniques ◽  
Cam Follower ◽  
Set Up

In this work we suggest a synthesis of recent results obtained on the application of soft-computing techniques to solve typical automatic machines design problems. Particularly, here we show an optimization method based on the application of a specialized algorithms ruled by a generalized software procedures, which appears able to help the mechanical designer in the first part of the design process, when he has to choose among different wide classes of solutions. In this frame, among the different problems studied, we refer here about the choice of the best class of motion profiles, to be imposed to a cam follower, which must satisfy prefixed design specifications. A realistic behaviour of the system is considered and the parameter model identification is set up by a soft computing procedure. The design, based on theoretical knowledge, sometimes is not sufficient to fulfil desired dynamical performances, in this situation, a residual optimization is achieved with the help of another optimizing method. The problem of a cam-follower design is presented. A class of motion profiles and the best theoretical motion profile is selected by an evolutionary algorithm. A realistic model is considered and its parameter identification is achieved by a genetic algorithm. The residual optimization is achieved by a servomotor optimized by another genetic algorithm. Evolutionary approach is used during all the design process and, as was shown, it allows really interesting performance in terms of simplicity of the design process and in terms of performance of the product.

scholarly journals Applicability of Cellular Automata in Cryptanalysis

Cryptography ◽  
2020 ◽  
pp. 180-191
Author(s):  
Harsh Bhasin ◽  
Naved Alam
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Cellular Automata ◽  
Literature Review ◽  
Soft Computing ◽  
Search Problem ◽  
Extensive Literature ◽  
Soft Computing Techniques ◽  
A New Technique ◽  
The Given

Cryptanalysis refers to finding the plaintext from the given cipher text. The problem reduces to finding the correct key from a set of possible keys, which is basically a search problem. Many researchers have put in a lot of effort to accomplish this task. Most of the efforts used conventional techniques. However, soft computing techniques like Genetic Algorithms are generally good in optimized search, though the applicability of such techniques to cryptanalysis is still a contentious point. This work carries out an extensive literature review of the cryptanalysis techniques, finds the gaps there in, in order to put the proposed technique in the perspective. The work also finds the applicability of Cellular Automata in cryptanalysis. A new technique has been proposed and verified for texts of around 1000 words. Each text is encrypted 10 times and then decrypted using the proposed technique. The work has also been compared with that employing Genetic Algorithm. The experiments carried out prove the veracity of the technique and paves way of Cellular automata in cryptanalysis. The paper also discusses the future scope of the work.

scholarly journals Performance Analysis of Genetic Algorithm, Particle Swarm Optimization and Ant Colony Optimization for solving the Travelling Salesman Problem

2019 ◽  
Vol 8 (2S4) ◽  
pp. 91-95
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Ant Colony Optimization ◽  
Soft Computing ◽  
Travelling Salesman Problem ◽  
Particle Swarm ◽  
Ant Colony ◽  
Travelling Salesman ◽  
Swarm Optimization ◽  
Soft Computing Techniques

The Travelling salesman problem also popularly known as the TSP, which is the most classical combinatorial optimization problem. It is the most diligently read and an NP hard problem in the field of optimization. When the less number of cities is present, TSP is solved very easily but as the number of cities increases it gets more and more harder to figure out. This is due to a large amount of computation time is required. So in order to solve such large sized problems which contain millions of cities to traverse, various soft computing techniques can be used. In this paper, we discuss the use of different soft computing techniques like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and etc. to solve TSP.

scholarly journals SOFT COMPUTING SYSTEM FOR THE DIAGNOSIS OF HORMONAL IMBALANCE

2020 ◽  
Vol 7 (6) ◽  
pp. 30-42
Author(s):  
Victor Ekong
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Medical Condition ◽  
Real Life ◽  
Computing System ◽  
Human Existence ◽  
Life Problems ◽  
Hormonal Imbalance ◽  
Soft Computing Techniques

Soft computing, as a science of modelling systems, applies techniques such as evolutionary computing, fuzzy logic, and their hybrids to solve real life problems. Soft computing techniques are quite tolerant to incomplete, imprecise, and uncertainty when dealing with complex situations. This study adopts a hybrid of genetic algorithm and fuzzy logic in diagnosing hormonal imbalance. Hormones are chemical messengers that are vital for growth, reproduction, and are essential for human existence. Hormones may sometimes not be balanced which is a medical condition that often go unnoticed and it’s quite difficult to be diagnosed by medical experts. Hormonal imbalance has several symptoms that could also be confused for other ailments. This proposed system serves as support for medical experts to improve the precision of diagnosis of hormonal imbalance. The study further demonstrates the effective hybridization of genetic algorithm and fuzzy logic in resolving human problems.

scholarly journals Kansei Information Processing in Multimedia Applying Intelligent Soft Computing Techniques

2000 ◽  
Vol 4 (6) ◽  
pp. 428-436 ◽  
Author(s):  
Takehisa Onisawa ◽  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Information Processing ◽  
Soft Computing ◽  
Set Theory ◽  
Fuzzy Set Theory ◽  
Interactive Genetic Algorithm ◽  
Fuzzy Measures ◽  
Soft Computing Techniques ◽  
Genetic Algorithm Approach

This paper mentions the concept of Kansei information that must be dealt with in multimedia. Kansei information has subjectivity, ambiguity, vagueness and situation dependence. This piece of information is not dealt with by the conventional natural science techniques. This paper also introduces soft computing techniques such as a neural network model, fuzzy set theory, a fuzzy measures and fuzzy integrals model, and the interactive genetic algorithm approach that are applied to Kansei information processing or some related problems.

Soft Computing Techniques for Identification of an Asynchronous Machine Parameters

2014 ◽  
Vol 626 ◽  
pp. 155-163
Author(s):  
R. Sridevi ◽  
C. Kumar ◽  
N. Iswarya ◽  
R. Gopikaramanan
Keyword(s):  
Genetic Algorithm ◽  
Parameter Estimation ◽  
Particle Swarm Optimization ◽  
Induction Motor ◽  
Soft Computing ◽  
Load Test ◽  
Artificial Immune ◽  
Swarm Optimization ◽  
Soft Computing Techniques ◽  
Equivalent Circuit Parameters

This manuscript discusses about the Parameter estimation of Induction motor by utilizing the soft computing methodologies that is by using evolutionary algorithms such as Genetic algorithm, Particle swarm optimization, Artificial immune algorithm to overcome the difficulties in the conventional method where we calculating the per phase equivalent circuit parameters from the No load test and Blocked rotor test which compromises in result in terms of accuracy of the result and also evaluated the accuracy of the different algorithm in estimating the parameters of the induction motor.

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