Brief Examples
from
Optimal Designs Enterprise

  • Increased productivity resulted from optimizing a software program that required 20 days per execution to less than 10 hours at Lockheed Missiles & Space Co.

  • Reducing circuit development time from 12 weeks to less than 1 week was another increased productivity example at Memorex Corp. Plus the solution was optimal. This circuit was called a Matched Filter where minimizing intersymbol interference (ISI) was the goal.

Mission Statement:
Get our FortranCalculus compiler operational and in use via the internet. Our free compiler simplifies solving math problems by minimizing code necessary to state & solve a problem. Some new thinking is necessary for those wanting to get the most for their buck; convert from simulation to optimization thinking.

What’s the different between simulation and optimization? Picture a saw horse construction project. A Simulation would yield A saw horse where Optimization would yield an Optimal saw horse. If the objective (function) was good and proper then the Optimal saw horse would be the best solution, right? For example, the objective might be lightest & strongest saw horse. A wrong objective might be just the strongest saw horse. This might yield a strong horse but a very heavy one.

Train Educators:
Modeling & Simulation’s next step is (Mathematical) Optimizations. Optimizations require an Objective (function). Today's Engineers & Scientists solve problems with a “Find X” mind-set. With some Operational Research training they could expand their thinking to a “Find X to Optimize Y” mind-set. Then they would be ready for Optimizations, Calculus-level programming, and software. (This would drop today’s design times that require months even man years to a few days! Manufacturing processes could be optimized to the days demand and thus maximize their profits.)

“Find X to Optimize Y” thinking among professors will cause most Engineering & Science textbooks to be rewritten with optimization examples and discussions. This will be great stuff for industries and government; applied engineering and/or science not just theories.



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