Novel genome coding of genetic algorithms for the system partitioning problem

The research field of partitioning for electronic systems started to attract significant attention of scientists about fifteen years ago. Gaining ever more importance due to the rampant growth and shortening design cycles in wireless embedded systems, a multitude of formulations for this problem has emerged. Accordingly, a similar multitude can be found in the number of strategies that address system partitioning. A large proportion of the applied strategies utilise the concept of genetic algorithms, or, when based on different strategies, usually compare themselves to standard implementations of genetic algorithms. In this work, the internal mechanisms of this optimisation technique are thoroughly investigated and severe shortcomings of standard implementations are identified. Beneficial observations are made with respect to chromosome coding and mutation dedicated to typical problem graphs revealing a significant impact on the obtained solution quality. New problem oriented codings and operators are introduced and their performance is demonstrated on a task graph set of relevant process graphs. Finally, the modified genetic algorithm competes against Wiangtong's tabu search, Axelsson's simulated annealing, and Kalavade's GCLP algorithm.