Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Microsystem design
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Formal engineering design synthesis
Automated surface micro-machining mask creation from a 3D model
Microsystem Technologies
Evolutionary design in a multi-agent design environment
Applied Soft Computing
System-level synthesis of MEMS via genetic programming and bond graphs
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Knowledge interaction with genetic programming in mechatronic systems design using bond graphs
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Evolved finite state controller for hybrid system
Proceedings of the first ACM/SIGEVO Summit on Genetic and 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
Hierarchical component-based representations for evolving microelectromechanical systems designs
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Solving system-level synthesis problem by a multi-objective estimation of distribution algorithm
Expert Systems with Applications: An International Journal
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In this paper, we discuss the hierarchy that is involved in a typical MEMS design and how evolutionary approaches can be used to automate the hierarchical synthesis process for MEMS. The paper first introduces the flow of a structured MEMS design process and emphasizes that system-level lumped-parameter model synthesis is the first step of the MEMS synthesis process. At the system level, an approach combining bond graphs and genetic programming can lead to satisfactory design candidates as system-level models that meet the predefined behavioral specifications for designers to trade off. Then at the physical layout synthesis level, the selection of geometric parameters for component devices and other design variables is formulated as a constrained optimization problem and addressed using a constrained genetic algorithm approach. A multiple-resonator microsystem design is used to illustrate the integrated design automation idea using these evolutionary approaches.