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首页> 外文期刊>Fuzzy Optimization and Decision Making: A Journal of Modeling and Computation Under Uncertainty >Numerical Approach of Multi-Objective Optimal Control Problem in Imprecise Environment
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Numerical Approach of Multi-Objective Optimal Control Problem in Imprecise Environment

机译:不精确环境下多目标最优控制问题的数值方法

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In this paper, realistic production-inventory models without shortages for deteriorating items with imprecise holding and production costs for optimal production have been formulated. Here, the rate of production is assumed to be a function of time and considered as a control variable. Also the demand is time dependent and known. The imprecise holding and production costs are assumed to be represented by fuzzy numbers which are transformed to corresponding interval numbers. Following interval mathematics, the objective function is changed to respective multi-objective functions and thus the single-objective problem is reduced to a multi-objective decision making(MODM) problem. The MODM problem is then again transformed to a single objective function with the help of weighted sum method and then solved using global criteria method, calculus method, the Kuhn-Tucker conditions and generalized reduced gradient(GRG) technique. The models have been illustrated by numerical data. The optimum results for different objectives are obtained for different types of production function. Numerical values of demand, production function and stock level are presented in both tabular and graphical forms.
机译:在本文中,已经制定了不短缺的现实生产库存模型,该库存不精确且持有不准确的物品变质,并且为实现最佳生产需要生产成本。在此,生产率被认为是时间的函数并且被认为是控制变量。需求也是时间相关的并且是已知的。假定不精确的持有和生产成本由模糊数表示,该模糊数被转换为相应的区间数。遵循区间数学,将目标函数更改为各自的多目标函数,从而将单目标问题简化为多目标决策(MODM)问题。然后,借助加权和方法将MODM问题再次转换为单个目标函数,然后使用全局准则方法,演算方法,Kuhn-Tucker条件和广义归一化梯度(GRG)技术进行求解。通过数值数据说明了模型。对于不同类型的生产函数,可以获得针对不同目标的最佳结果。需求,生产函数和库存水平的数值以表格和图形形式显示。

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