Random optimization is the name applied to a class of algorithms which can be used to solve optimization problems.
Random optimization is relatively little known, but can be compared with genetic algorithms, and often random optimization outperforms other methods with significantly faster convergence.
Optimization has been used for forty years in microwave CAD programs to flatten gain, increase bandwidth, improve stability, or fix any problem most problems that can be expressed mathematically from circuit S-parameters.
Optimization is when you use linear analysis software to vary the values of certain elements within the schematic (selected by the user) in an attempt to improve the overall response.
Randomoptimization is the equivalent of an infinite number of monkeys on an infinite number of computers.
A one-dimensional placement and routing optimizer is developed for the Garp Gate Array RISC Processor, using a greedy algorithm to minimize total vertical wire length.
A precise formulation of the placement optimization problem must capture the intent that communication between rows is to be "localized" to use the shortest wires possible.
The analyses are pessimistic in that the optimizer may reach an illegal final configuration after missing a legal intermediate configuration, but the analyses capture the minimum performance to be expected from the optimizer.
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