Object-Oriented Programming for Genetic Algorithm Solver

This project focuses on implementing object-oriented design for a genetic algorithm solver using c++ program. It involves analyzing data variables and designing data in parallel. The project includes conceptual models, use cases, system sequence diagrams, rational data models, and user interfaces. The output is based on input source data files and includes generation value, best value, fitness value, and more.

Object-Oriented Programming

Table of Contents
Introduction.........................................................................................................................................1
Input and Output.................................................................................................................................1
Object oriented Design........................................................................................................................1
UML class Diagram.............................................................................................................................2
Conclusion............................................................................................................................................3

Introduction
In this project, have to implement the object-oriented design for genetic algorithm
solver using c++ program. It is used to analysis the data variable and to design the data in
parallel. It includes the conceptual model, use case, system sequence diagram, rational data
model and user interface. These models are used for input source and get the output based on
the data file. The data file contains the 36 different variables on both files. To analyse the
genetic algorithm solver for that given data variable and implement the best value, generation
value and fitness value for that variable.
Input and Output
There are two text files which are used to implement the genetic algorithm solver
using c++. Import the text file on program code and this will implement the genetic
algorithm. The output file is based on the two-text file. The output contains the generation
value, best value, average value, fitness and standard deviation value. We have to calculate
the total variable for 100 generation and analyse the best fitness value from the dataset.
Object oriented Design
The object-oriented design has some features for implementation that are built into the
programming language. The features are class, informationhiding, inheritance, interface and
polymorphism. Theobject-oriented design model is providing the output of object-
orientedanalysis. Itanalysis the data and the design. Theinput source model for the object-
oriented design such as conceptual model uses the casemodel, system sequence model,
userinterface and rational data model. Theconceptual model is mainly used for capturing the
problem domain and then it chooses the independent variable for implementation. Usecase
model for describing the sequences of events that interact with user called as actor.
Itidentifies the user and processes that performance.Another one is the sequence model that
model is used forimplementingthescenariofor use incasemodel. The user interface is used to
visualize the end product that shows and also describe the look and feel of end product of this
user interface. Thenext model is rational model, used for storing the data from the user. These
models are input sources of object-oriented design.

UML class Diagram
This diagram contains the used class diagram and the current package diagram. The
used class diagram contains the DMtx, NPR, QR, and other data. The current package
diagram contains the population data, genetic member data and other data. The population
data is connected to the genetic data which is used for analysing the generation and the best
value. The population package contains the list of the genetic member data, other data,
evaluation,mutation, crossover and other method and that method are used to calculate the
generation value based on input sources. The genetic member value contains the cross over,
mutate and solve the mainvalue that is depended on NPR data, QR data, ensemble data and
NN genetic data. The current package data is depended on the used class diagram. These data
are used to calculate the generation value, best value and fitness value from input source file.

Conclusion
The genetic solver algorithm is successfully implemented by using c++ program. The
data file is imported by using c++ code and it analysis the generation value, best value and
fitness value. The data file contains the 36 different variables on both the files. The class and
interface features are used for that algorithm. Finally, the genetic solver algorithm is
successfully implemented.