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A Multiobjective Multi-Item Inventory Control Problem in Fuzzy-Rough Environment Using Soft Computing Techniques

机译:模糊粗糙环境下的多目标多项目库存控制问题的软计算技术

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The optimal production and advertising policies for an inventory control system of multi-itemmultiobjective problem under a single management are formulated as an optimal control problem with resourceconstraints under inflation and discounting in fuzzy rough (Fu-Ro) environment. The objectivesand constraints in Fu-Ro are made deterministic using fuzzy rough expected values method (EVM). Here,the production and advertisement rates are unknown and considered as control (decision) variables. Theproduction, advertisement, and demand rates are functions of timet. Maximization of the total proceed fromperfect and imperfect units and minimization of the total cost consisting of production, holding, and advertisementcosts are formulated as optimal control problems and solved directly using multiobjective geneticalgorithm (MOGA). In another method for solution, membership functions of the objectives are derived andthe multi-objective problems are transformed to a single objective by the convex combination of the membershipfunctions and then the problem is solved by generalized reduced gradient (GRG) method. Finally, numerical experimentand graphical representation are provided to illustrate the system.
机译:在模糊粗糙(Fu-Ro)环境下,在通货膨胀和折扣下具有资源约束的多项目多目标库存控制系统的最优生产和广告策略被制定为最优控制问题。使用模糊粗略期望值方法(EVM)确定Fu-Ro中的目标和约束。在这里,生产和广告率是未知的,并被视为控制(决策)变量。生产,广告和需求率是时间的函数。最佳和不完美单位的总收益最大化以及生产,持有和广告成本的总成本收益最小化被制定为最优控制问题,并直接使用多目标遗传算法(MOGA)解决。在另一种解决方法中,导出目标的隶属度函数,然后通过隶属度函数的凸组合将多目标问题转换为单个目标,然后通过广义降梯度(GRG)方法解决该问题。最后,通过数值实验和图形表示对系统进行了说明。

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