The objective in this project is to optimize a given circuit using Genetic Algorithm. The parameter which will be optimized can be chosen by the user and the program will change the specified parameters to reach the desired accuracy. The first step is to be able to fit a function to desired values, this has been done for a specified function as an example in the Fit_Function program. The next step is to find a Simulator which simulates the specified circuit and returns the symbolic transfer function of the circuit, or else we would have to run a numerical simulator like PSPICE in each iteration and that is going to make the optimization process take a much longer time to complete.And the final step is to link the main program to this simulator.


About Optimization using Genetic Algorithm:


The rapidly expanding field of Genetic Algorithms ( GAs ) has given rise to many new applications in a variety of disciplines. One of the major applications in which GA is used is
Optimization. Genetic Algorithm is a subset of evolutionary algorithms that model biological processes to optimize highly complex cost functions.

Some of the advantages of a genetic algorithm include that it :

• Optimizes with continuous or discrete parameters
• Doesn't require derivative information
• Simultaneously searches from a wide sampling of the cost surface
• Deals with a large number of parameters
• Is well suited for parallel computers
• Optimizes parameters with extremely complex cost surfaces; they can jump out of a local minimum
• Provides a list of optimum parameters, not just a single solution
• May encode the parameters so that the optimization is done with the encoded parameters
• Works with numerically generated data, experimental data, or any analytical functions.

About The Project:

Project supervisor, Dr Naser Sadati, has been a great mentor and has actually thought us everything we know about Fuzzy Logic and Genetic algorithm.


The project group is consisted of :

• Arsham Hatambeiki , BS student, Electronics Group, Sharif University of Technology
• Saeed Karimi Fard , BS student , Control Group , Sharif University of TechnologyThis application is written in Microsoft Visual C++ 6.0 - 09 November, 2001

Attached is a complete introduction to Genetic Algorithm and Otimization and the special ( in Farsi ) changes made for our optimizer. The last section of the pdf is a complete tutorial for the ACO software and some screen shots ( in English ) .