摘要：Optimizing the design of devices that belongs to Micro Electro Mechanical System (MEMS) technology is turning out to be a main area of research currently. Several algorithms are available to produce an optimized design of MEMS. The MEMS accelerometer may be scheduled using parameters that include Beam length, Beam width, Beam depth, Beam mass, proof mass and so on. This study is chiefly involved in the optimization of design parameters like die area and a novel parameter called as Force. Artificial Bee Colony (ABC) optimization and Particle Swarm Optimization (PSO) are the two algorithms that are used to optimize these parameters. The ABC performs the primary optimization and PSO does the optimization of the fitness solution resulting from the execution of ABC algorithm. Employing the two optimization algorithms in a combined way yields improved optimized parameters, which are engaged in the efficient design of MEMS accelerometer.
