Optimal Design Centring Through a Hybrid Approach Based on Evolutionary Algorithms and Monte Carlo Simulation
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- Pierluissi L., Rocco S. C.M. (2007) Optimal Design Centring Through a Hybrid Approach Based on Evolutionary Algorithms and Monte Carlo Simulation. In: Beliczynski B., Dzielinski A., Iwanowski M., Ribeiro B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4431. Springer, Berlin, Heidelberg
In many situations a robust design could be expensive and decision-makers need to evaluate a design that is not robust, that is, a design with a probability of satisfying the design specifications (or yield) less than 100 %. In this paper we propose a procedure for centring a design that maximises the yield, given predefined component tolerances. The hybrid approach is based on the use of Evolutionary Algorithms, Interval Arithmetic and procedures to estimate the yield percentage. The effectiveness of the method is tested on a literature case. We compare the special evolutionary strategy (1+1) with a genetic algorithm and deterministic, statistical and interval-based procedures for yield estimation.
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