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Parameter-Guided Optimization Algorithm and Its Application in Designing a Rice Transplanting Mechanism

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  131586344,  2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: @2013
Authors:   Yun Zhao, Xiaoqiang Du
Keywords:   Parameter-guided optimization algorithm Variable step-size optimization Rice transplanting mechanism.

Abstract. A new algorithm to address complex optimization issues that have multiparameter, multiobjective, strong coupling features is proposed in this paper. It is named parameter-guided optimization algorithm. In this algorithm, the objective functions should be established by theoretical analysis at first. Secondly, the objective function whose calculated value deviates most from the ideal value is identified. Thirdly, the most sensitive parameter of the identified objective function that could result in the least difference between the identified objective function and the ideal value is identified and adjusted with variable step-size by assuming that the parameter is linear with the objective function. Finally, the adjusted parameter is set as the initial value to repeat the optimization cycle until the error between the calculated value and the ideal value of each objective function is less than the convergence threshold. An optimization program was developed based on the proposed algorithm. Optimal parameters for the transplanting mechanism in a riding-type rice transplanter were calculated by the program.

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