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Description of Lindo What’sBest 19.0.1.2
Lindo What’sBest 19.0.1.2 is an add-in to Excel that allows you to build large scale optimization models in a free form layout within a spreadsheet. What’sBest! combines the proven power of Linear, Nonlinear (convex and nonconvex/Global), Quadratic, Quadratically Constrained, Second Order Cone, Semi-Definite, Stochastic, and Integer optimization with Microsoft Excel — the most popular and flexible business modeling environment in use today. The recently released What’sBest! 19 includes a number of significant enhancements and new features.
Key Benefits of Lindo What’sBest 19.0.1.2
The World’s Most Powerful Solver for Microsoft Excel
– What’sBest! will efficiently solve your biggest, toughest models. The linear, integer, nonlinear and global solvers in What’sBest! have been designed for large scale commercial use and field tested on real world models by companies around the world. For optimization modeling in Excel, What’sBest! offers unrivaled speed and capacity.
Modeling is Fast and Easy
– Excel users will find What’sBest! to be an easy and powerful tool for solving optimization problems. Most users are able to begin modeling within minutes of installation.
Build Models for your Clients
– What’sBest! is an ideal tool for creating optimization applications for use by others. What’sBest! allows you to provide the application in a form that is best suited to the user. For managers, you can build a simple, easy-to-understand spreadsheet. For clerical workers, you can create turn-key applications with custom interfaces.
Extensive Documentation and Help
– What’sBest! provides all of the tools you will need to get up and running quickly. You get the What’sBest! User Manual (in printed form and available via the online Help) that fully describes the commands and features of the program. Also included in the manual is discussion of the major classes of linear, integer and nonlinear optimization problems along with over two dozen real world based examples that you can modify and expand.
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