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Performance Improvement of Tea Industry with Multi Objective Particle Swarm Optimisation

机译:基于多目标粒子群算法的茶产业绩效提升

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In this Paper the Multi-Objective Particle Swarm Optimisation has been used to demonstrate ways to improve the efficiency of Tea Industry after implementation in MAT-LAB. The data for Terai Tea Estate has been extracted from the Financial Statements obtained from Tea Board. The ratio functions have been identified, whose maximisation will improve the performance of the organisation. The regression analysis has been performed to estimate the coefficients of two ratio functions. The Pareto Front has been derived for this dual objective function using Multi-Objective Particle Swarm Optimisation. The results have been presented in this paper.
机译:在本文中,多目标粒子群优化已被用于演示在MAT-LAB中实施后提高茶产业效率的方法。 Terai Tea Estate的数据摘自从Tea Board获得的财务报表。比率函数已经确定,其最大化将改善组织的绩效。已经进行了回归分析以估计两个比率函数的系数。使用多目标粒子群优化算法为该双目标函数导出了Pareto前沿。结果已在本文中提出。

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