## GenSheet

** Category** Intelligent Software>Genetic Algorithm Systems/Tools

** Abstract** GenSheet implements genetic algorithms as C programs
dynamically linked to Microsoft Excel spreadsheets. In GenSheet, a
gene is a spreadsheet cell, a chromosome (vector x) is range of
spreadsheet cells, and a population is a rectangular region of
spreadsheet cells (an array of chromosomes). GenSheet runs under
all implementations of Microsoft Excel (version 4.0 or higher), including
Windows, Macintosh, and Sun under Solaris. GenSheet macros
interface with all Excel spreadsheet commands for charting, for
spreadsheet formatting and for reporting and printing.

GenSheet supports genetic operations for binary, integer, and real, and permutation representations, and includes special commands for constrained nonlinear optimization (integer and non-linear programming), genetic classifiers, job-shop scheduling, and minimum variance portfolio computation.

Using Microsoft Excel as the user interface, all GenSheet commands are configured in an easy-to-use Excel menu-bar that is integrated with all standard Excel commands and charting utilities. GenSheet provides an interactive help and a tutorial that takes you through the process of building applications using genetic algorithms.

Additional features include:

Input/Output - Genetic algorithm inputs consist of your specification of an objective function to be maximized, and parameters that determine how the genetic algorithm is to "breed" improved solutions from a population of parent solutions. In GenSheet, you specify the initial population, parameters (such as number of generations and mutation rate), and other inputs directly as spreadsheet regions. GenSheet output is the display of the population after computation.

Size and Speed - GenSheet limits the population size to a maximum of 1000 individuals, having at most 256 fields. Run-time speed depends on the hardware support for floating point computation.

GenSheet supports a comprehensive set of genetic representations, operations, and utilities, all packaged in an easy-to-use system based on Excel Menus and dialogs:

- 1) Numerical Representations - Binary, Integer, Real, Permutation (see detail info below).
- 2) Genetic Operations - Uniform, Partially Matched Crossovers, Average, Coarse, Fine Crossovers, Ordinal/Positional Mutations.
- 3) Data Preprocessing Utilities - Representing Text and Numbers as Binary, Scaling (see detail info below).

GenSheet supports the following algorithms and utilities

- 1) Binary - The basic genetic algorithm, representing genes as arrays of bits.
- 2) Integer - Genes as arrays of integers. Useful for integer programming problems.
- 3) Real - Genes as arrays of real numbers. Useful for non-linear programming.
- 4) Permutation - Genes as arrays of integers, where order is significant.
- 5) Optimum Portfolio - A genetic algorithm for computing a minimum variance portfolio that maximizes return.
- 6) Genetic Scheduler - A genetic algorithm for sequencing a set of tasks whose order minimizes costs.
- 7) Genetic Classifier - A genetic algorithm for discovering rules, based on a set of sample cases.
- 8) AutoScale - Normalizes inputs to values between 0 and 1.
- 9) Text To Binary - Maps text to bit vectors.
- 10) Numbers to Binary - Maps numbers to bit vectors.

Sample Applications included in GenSheet:

1) Optimum Portfolio Application - How do you allocate the proportions in a portfolio of stocks in a way that maximizes the portfolio return and minimizes the portfolio risk? Input to GenSheet includes a vector of expected returns for the individual stocks and a covariance matrix relating the returns to each other (used to compute portfolio risk). This is a quadratic programming problem.

2) Task Scheduling Application - How do you schedule a sequence of tasks in a way that minimizes the total cost of the schedule? Input to GenSheet includes a vector of costs for each task, and a dependency matrix that shows if one task can be performed before the other, and if tasks can be executed concurrently. This application is a combinatorial problem related to the classic Traveling Salesman Problem.

3) Genetic Classifier Application - How can you learn rules from a set of examples? Input to GenSheet includes a region of cases; output shows the induced rules, listed by strength.

Licenses - The basic single-user license includes the genetic algorithm development tools integrated with the Microsoft Excel user inteface macros and dynamic link libraries; an on-line tutorial; a 100 Page Manual; function optimization templates; and sample Applications. GenSheet comes with E-mail Technical Support.

*System Requirements*

GenSheet requires Microsoft Excel.

*Manufacturer*

- Inductive Solutions, Inc.
- 380 Rector Place, Suite 4A
- New York, New York 10280
- Email: info@inductive.com
- Telephone: +1 (212)945.0630
- Fax: +1 (212)945.0367

** Manufacturer Web Site** Inductive Solutions, Inc.

** Price** Student version $45; inquire for additional pricing.

** G6G Abstract Number** 20045

** G6G Manufacturer Number** 101400