Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Microsystem design
3D game engine design: a practical approach to real-time computer graphics
3D game engine design: a practical approach to real-time computer graphics
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
A novel approach to multi-level evolutionary design optimization of a MEMS device
ICES'10 Proceedings of the 9th international conference on Evolvable systems: from biology to hardware
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An automated design synthesis system based on a multi-objective genetic algorithm (MOGA) has been developed for the optimization of surface micromachined MEMS devices. A hierarchical component-based genotype representation is used, which incorporates specific engineering knowledge into the design and optimization process. Each MEMS component is represented by a gene with its own parameters defining its geometry and the way it can be modified from one generation to the next. The object-oriented genotype structures efficiently describe the hierarchical nature typical of engineering designs. They also prevent MOGA from wasting time exploring inappropriate regions of the search space. The automated MEMS design synthesis is demonstrated with surface-micromachined resonator and accelerometer designs.