Design optimization using Genetic Algorithm and Cuckoo Search

Genetic algorithm (GA) is widely used for embedded system design optimization. GA needs repeated evaluation of fitness function, but for complex embedded systems fitness function evaluation is costly as it includes multiple objectives. A recently proposed Cuckoo Search (CS) method does not require repeated evaluation of fitness function and can provide a set of optimal solutions within a reasonable time. This paper compares the application of GA and CS algorithm to the problem of design space exploration and discusses their empirical comparison.

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