基于多目标粒子群优化的茶叶产业绩效提升

D. Roy, R. Dasgupta
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引用次数: 0

摘要

本文运用多目标粒子群优化方法,在MAT-LAB中实现了对茶叶行业效率的提高。寺井茶业的数据是从茶叶委员会获得的财务报表中提取的。比率函数已经确定,其最大化将提高组织的绩效。对两个比值函数的系数进行了回归分析。利用多目标粒子群算法,推导了该双目标函数的Pareto Front。本文给出了实验结果。
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Performance Improvement of Tea Industry with Multi Objective Particle Swarm Optimisation
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.
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