Kumara Sastry » Source Code

Single and multiobjective genetic algorithm toolbox for Matlab in C++

Kumara Sastry — Mon, 11 Jun 2007 19:48:11 +0000

Sastry, K. (2007). IlliGAL Report No. 2007017. University of Illinois at Urbana-Champaign, Urbana IL. [Documentation - PDF] [Documentation - PS] [Download source code].

Abstract:
This report provides documentation for the general purpose genetic algorithm toolbox for matlab in C++. The fitness function used in the toolbox is written in matlab. The toolbox provides different selection, recombination, mutation, niching, and constraint-handling operators. Problems with single and multiple objectives can be solved with the toolbox. Moreover, the toolbox is easily extensible and customizable for incorporating other operators and for solving user-defined search problems.

Single and Multiobjective Genetic Algorithm Toolbox in C++

Kumara Sastry — Mon, 11 Jun 2007 19:43:43 +0000

Sastry, K. (2007). IlliGAL Report No. 2007016. University of Illinois at Urbana-Champaign, Urbana IL. [Documentation - PDF] [Documentation - PS] [Download source code].

Abstract:
This report provides documentation for the general purpose genetic algorithm toolbox. The toolbox provides different selection, recombination, mutation, niching, and constraint-handling operators. Problems with single and multiple objectives can be solved with the toolbox. Moreover, the toolbox is easily extensible and customizable for incorporating other operators and for solving user-defined search problems.

Extended compact genetic algorithm in matlab

Kumara Sastry — Fri, 23 Mar 2007 05:17:03 +0000

Sastry, K., Orriols-Puig, A. (2007). IlliGAL Report No. 2007009. University of Illinois at Urbana-Champaign, Urbana IL. [Documentation - PDF] [Documentation - PS] [Download source code].

Abstract:
This report provides documentation for matlab^® implementation of the extended compact genetic algorithm (eCGA). The implementation works for integer decision variables where each variable can be of differing cardinality.

Generator and interface for random decomposable problems in C

Kumara Sastry — Sat, 08 Apr 2006 14:32:47 +0000

Pelikan, M., Sastry, K., Butz, M. V., Goldberg, D. E. (2006). MEDAL report no. 2006003. University of Missouri-St. Louis. [Documentation - PDF] [Download source code] .

Abstract
This technical report describes how to download, compile and use the C source code of the generator of random additively decomposable functions and the functions that enable the use of the generated instances in any standard optimization algorithm.

χ-ary extended compact genetic algorithm for matlab in C++

Kumara Sastry — Sun, 26 Mar 2006 21:46:09 +0000

Sastry, K., de la Ossa, L., Lobo, F. G. (2006). IlliGAL report no. 2006014. University of Illinois at Urbana Champaign. [Documentation - PDF] [Documentation - PS] [Download source code].

Abstract:
This report provides documentation for the χ-ary extended compact genetic algorithm (χECGAm) for matlab in C++ that solves problems with χ-ary alphabets. The fitness function used in the χECGAm is written in matlab. The source code is an extension of the original binary-coded extended compact genetic algorithm (ECGA) (Harik, 1999) and its previous implementation in C++ (Lobo & Harik, 1999; Lobo, Sastry, & Harik, 2006). Each decision variable in the current implementation can be of different cardinalities and the χECGAm finds linkage groups among the decision variables

χ-ary extended compact genetic algorithm in C++

Kumara Sastry — Sun, 26 Mar 2006 21:21:45 +0000

de la Ossa, L., Sastry, K., Lobo, F. G. (2006). IlliGAL report no. 2006013. University of Illinois at Urbana Champaign. [Documentation - PDF] [Documentation - PS] [Download source code].

Abstract:
This report provides documentation for the χ-ary extended compact genetic algorithm (χECGA) that solves problems with χ-ary alphabets. The source code is an extension of the original binary-coded extended compact genetic algorithm (ECGA) (Harik, 1999) and its previous implementation in C++ (Lobo & Harik, 1999; Lobo, Sastry, & Harik, 2006). Each decision variable in the current implementation can be of different cardinalities and the χECGA finds linkage groups among the decision variables.

Extended compact genetic algorithm in C++: Version 1.1

Kumara Sastry — Sun, 26 Mar 2006 21:15:15 +0000

Lobo, F. G., Sastry, K., Harik, G. R. (2006). IlliGAL report no. 2006012. University of Illinois at Urbana Champaign. [Documentation - PDF] [Documentation - PS] [Download source code].

Abstract
This report provides documentation for version 1.1 of the extended compact genetic algorithm (ECGA). Version 1.1 uses Mersenne Twister for the pseudo random number generator and is compliant with GCC 3.4 and 4 series.