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This zip file contains the Presentation (PDF) and M-files that were demonstrated in the MathWorks Webinar: Using Genetic Algorithms in Financial Applications delivered on Dec 11 2007.

The purpose of the webinar was to highlight how Genetic Algorithms may be used to supplement portfolio optimization problems. The Genetic Algorithm contains custom evolution algorithms that were built specifically for this webinar. They allow the user...



SpeedyGA is a vectorized implementation of a genetic algorithm in the Matlab programming language. Without bells and whistles, it faithfully implements the specification for a Simple GA given on pgs 10, 11 of M. Mitchell's GA book. See comments in...



PID controller has been extensively used in the industrial world. But in this controller it is difficult to tune the PID gains.

We apply the genetic algorithm(GA) to tune the PID gains. The GA is agorithm using the biotic; gene the...



A framework for utilising the Genetic Algorithm in the domain of Game Theory



Solution for the Travelling Salesman Problem using genetic algorithm. Speed, particularly at large data volumes, is of essence. The project uses advanced variants of cross-over and mutation algorithms in order to expedite search in the solution...



Unit tests-based Genetic Programming in Java. The developer specifies unit tests, and the tool will use GP to evolve software that passes those tests.



Open Legacy Storage Document: Generic Document Archiving on Disk and Network(using MINA) Framework in Java for huge number of docs(up to 2^192 documents), efficient(Java NIO), crypto, net transfert, web retrieve, J2EE and eMail archiving compatible.



We use the genetic algorithm (gatool) to determine the four parameters of the implicit Forst-Kalkwarf-Thodos Model. Predictions are in perfect agreement with data of vapour pressure of iodobenzene versus temperature for a temperature range from...



We use the genetic algorithm (gatool) to determine the three parameters of the simple Antoine equation and the six parameters of the Modified Antoine Model. Predictions are in perfect agreement with experimental data of vapor pressure of ethanol...



This code proposes genetic algorithm (GA) to optimize the point-to-point trajectory planning for a 3-link (redundant) robot
arm. The objective function for the proposed GA is to minimizing traveling time and space, while not exceeding a...



it is used for genetic algorithm implementation for scheduling in wireless sensor networks



Files used in the Webinar "Developing a Financial Market Index Tracker using MATLAB OOP and Genetic Algorithms"

The zip file contains the data and files used to develop an application to track a market index using Genetic...



An object oriented library of an Genetic Algorithm, implemented in Java. Clear separation of the several concepts of the algorithm, e.g. Gene, Chromosome, Genotype, Phenotype, Population and Fitness Function. The fitness calculation is parallelized.



Galapagos is a Genetic Algorithm framework written in Java 5 with the intended audience of undergraduates in an Artificial Intelligence class. The goal of Galapagos is usability: a competent student should be able to learn this library in an...



The Genetic Algorithm Utility Library (or, GAUL for short) is a flexible programming library designed to aid in the development of applications that use genetic, or evolutionary, algorithms. It provides data structures and functions for handling...



This API is intended to help developers use genetic algorithms in their own java applications. GeneticLibrary.zip contains the netbeans project of the API itself. GeneticTrial.zip contains another netbeans project which is an example explaining...



Extended compact genetic algorithm (ECGA) is an algorithm that can solve hard problems
in the binary domain. ECGA is reliable and accurate because of the capability of
detecting building blocks, but certain difficulties are encountered...



Here in this program i designed a digital equalizer for noisy non linear channel using lms algorithm.

Description of program:
I made program for 2 channel filters and 3 functions of non linearity. equalizer is modeled from the...



N-queen generalized genetic algorithm. Parameters can be changed and tested.
It has very basic but effective functions of selection,crossover and mutation.
Queens are randomly positioned in the beginning.
I have written it for...



Use the mixed-integer genetic algorithm to solve an engineering design problem.
Designs often require that components come from a list of available sizes. In this example, we show how the Genetic Algorithm can be used to find values for the...