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Home : Company : Maplesoft Webinars : Web Seminar Categories : Online Webinar : Optimization and Analysis using Maple

Optimization and Analysis using Maple

Maplesoft
December 9, 2008: 2:00 PM - 3:00 PM (UTC-05:00) Eastern Time (US & Canada) Related Products

Many scientific and engineering applications have to obey tight performance tolerances. Initial designs are often sub-optimal, and to arrive at better operating conditions, manual iterative processes using, for example, calculators or spreadsheets, are applied. This can take many hours, or even days. Often the solution obtained through such processes is still far from adequate. Over the last few decades, software tools boasting advanced nonlinear systems modeling and optimization algorithms have become significantly simpler to use, and no longer require specialized knowledge; this has accelerated the productivity of technical professionals across all domains. With Maple, you can take the result of over twenty-five years of continual investment in basic research and design to better model and optimize scientific and engineering designs in less time.

This webinar will demonstrate, through several applications, how Maple provides an easy-to-use environment for advanced modeling and optimization. Within Maple, you can take advantage of some of the most advanced optimization techniques in the world. In addition, Maple provides thousands of functions for integral transforms, ODE, PDE, and DAE solving, linear algebra, statistics, signal processing, and much more. Maple’s computational engine can tackle your most complex mathematical problems.

You will also see how the Global Optimization Toolbox (GOT) can be used with Maple. Through the use of advanced optimization algorithms, the Global Optimization Toolbox finds the best solution for models that have many possible (local and “true” global) solutions. Maple and the GOT support a consistent modeling and optimization framework that not only delivers a solution in seconds or minutes, but is also based on rigorous mathematical techniques that ensure a global search based numerical approximation of the best possible solution.

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