Research on the key techniques of form and position evaluation based on the genetic algorithm

Changcai Cui; Bing Li

doi:10.1117/12.716377

13 October 2006 Research on the key techniques of form and position evaluation based on the genetic algorithm

Changcai Cui, Bing Li

Proceedings Volume 6280, Third International Symposium on Precision Mechanical Measurements; 62802H (2006) https://doi.org/10.1117/12.716377
Event: Third International Symposium on Precision Mechanical Measurements, 2006, Urumqi, China

Abstract

The Evolutionary Algorithm (EA)-Genetic Algorithm (GA) was improved to evaluate the form and position errors that were summarized as nonlinear optimization problems. The key techniques in the implementation of the GA have been studied in detail. The emphasis was on the fitness functions of the GA concerned with the concrete problem so that they were proposed first. Second the expression of the desired solutions was discussed in the continual space optimization problem. Because different expression was suitable for different problem, here the real numbers were used to express the solutions to find which were called as chromosomes in the GA. Third the improved evolutionary strategies of GA were described respectively on emphasis. They were the selection operation of Odd Number Selection plus Roulette Wheel Selection, the crossover operation of Arithmetic Crossover Between Near Relatives and Far Relatives, and the mutation operation of Adaptive Gaussian mutation. The evolutionary strategies determined the update of the whole population and the terminal solution. After operations from generation to generation, the initial stochastic population on the basis of the least squared solutions would be improved until the best chromosome/individual appeared. Finally some examples were computed to verify the devised method. The experimental results show that the GA-based method can find the desired solutions that are superior to the least squared solutions and almost equal to those given by other optimization techniques except a few examples give a similar result.

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Changcai Cui and Bing Li "Research on the key techniques of form and position evaluation based on the genetic algorithm", Proc. SPIE 6280, Third International Symposium on Precision Mechanical Measurements, 62802H (13 October 2006); https://doi.org/10.1117/12.716377

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KEYWORDS

Optimization (mathematics)

Genetic algorithms

Global Positioning System

Evolutionary algorithms

Error analysis

Manufacturing

Stochastic processes

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