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A Novel Approach to Optimization Problem without Objective Function

机译:无目标函数的优化问题新方法

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For optimization problem in complex systems, normally, the objective funtion is hardly obtained or quantified. In this paper, a novel approach is presented.Its first procedure is to model the objective function by fitting complete data with NN. Secondly, global optimization solutions would be searched for the fitted objective function with genetic algorithm (GA).Moreover, Peaks function inside MATLAB and actual PID control system were selected to demostrate the approach, respectively. The results show that the optimal values and the correspnding solutions between original function and fitted function were both very close. Therefore, the methodology, which combines modeling approach NN with global optimization algorithm GA, could effectively solve optimization problem without objective function.
机译:对于复杂系统中的优化问题,通常很难获得或量化目标功能。本文提出了一种新颖的方法,其第一步是通过将完整数据与NN拟合来对目标函数进行建模。其次,利用遗传算法(GA)寻找全局最优解,以寻找拟合的目标函数。此外,分别选择MATLAB内部的Peaks函数和实际的PID控制系统来演示该方法。结果表明,原始函数和拟合函数之间的最优值和对应解都非常接近。因此,该方法将建模方法NN与全局优化算法GA相结合,可以有效地解决没有目标函数的优化问题。

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