An Efficient Multi-Objective Genetic Algorithm for MEMS Tuning

Abstract:

Micro-electromechanical switches (MEMS) with good performance in high frequency application such as linearity, no DC power consumption, no noise, small size and capability to co-fabrication on the chip today, it is noteworthy. the evolutionary approach in the design optimization of MEMS is a novel and promising research area. The problem is of a multi-objective nature; hence, multi-objective evolutionary algorithms (MOEA) are used. In this paper we introduced geometrical parameters of micro-electromechanical switch as input parameters or variables of multi-objective genetic algorithms then we compute electrical parameter of mems switch That show good performance and relation between theoretical parameter and simulated results is good.

• Periodical: Advanced Materials Research (Volumes 622-623)
• Pages: 1353-1356
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.622-623.1353
• Online since: December 2012
• Authors: Mohammad Mojtaba Sheikholeslami, Hamid Reza Deihimfar, Khalil Mafinezhad, Iman Ahadi Akhlaghi
• Keywords: Genetic Algorithm (GA), Microelectromechanical Switchs, MOGA, Scattering Parameter

References

[1] Fujita, H.: Two Decades of MEMS– from Surprise to Enterprise. In: Proceedings of MEMS, Kobe, Japan, January 21-25 (2007).

[2] Hsu, T.R.: MEMS and Microsystems, 2nd edn. Wiley, Chichester (2008).

[3] Isoda, T., Ishida, Y.: Seperation of Cells using Fluidic MEMS Device and a Quantitative Analysis of Cell Movement. Transactions of the Institute of Electrical Engineering of Japan 126(11), 583–589 (2006).

DOI: 10.1541/ieejsmas.126.583

[4] Hostis, F. l., Green, N.G., Morgan, H., Akaisi, M.: Solid state AC electro osmosis micro pump on a Chip. In: International Conference on Nano science and Nanotechnology, ICONN, Brisbane, Qld, July 2006, p.282–285 (2006).

DOI: 10.1109/iconn.2006.340607

[5] Farnsworth M, Benkhelifa E, Tiwari A, Zhu M.: A novel approach to multi-level evolutionary design optimization of a MEMS device. Evolvable systems: from biology to hardware, LNCS 6274: 322–334, p.322–334, (2010).

DOI: 10.1007/978-3-642-15323-5_28

[6] Hao, Y., Zhang, D.: Silicon-based MEMS process and standardization. In: Proceedings of the 7th International Conference on Solid-State and Integrated Circuits Technology 2004, vol. 3, p.1835–1838 (2004).

DOI: 10.1109/icsict.2004.1435192

[7] Fedder, G.: Structured Design of Integrated MEM. In: Twelfth IEEE International Conference on Micro Electro Mechanical Systems, MEMS 1999, Orlando, FL, USA, p.1–8 (1999).

DOI: 10.1109/memsys.1999.746742

[8] Senturia, S.D.: Microsystem Design. Kluwer Academic Publishers, Dordrecht (2001).

[9] Haronain, D.: Maximizing microelectromechanical sensor and actuator sensitivity by optimizing geometry. Sensors and Actuators A 50, 223–236 (1995).

DOI: 10.1016/0924-4247(95)01086-6

[10] Iyer, S., Mukherjee, T., Fedder, G.: Automated Optimal Synthesis of Microresonators. In: Solid-State Sensors and Actuators, Chicago, IL, p.12–19 (1997).

DOI: 10.1109/sensor.1997.635395

[11] Kamalian, R., Zhou, N., Agogino, A.M.: A Comparison of MEMS Synthesis Techniques. In: Proceedings of the 1st Pacific Rim Workshop on Transducers and Micro/Nano Technologies, Xiamen, China, July 22-24, p.239–242 (2002).