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Hybrid genetic algorithms and line search method for industrial production planning with non-linear fitness function

机译:具有非线性适应度函数的工业生产计划的混合遗传算法和线搜索方法

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Many engineering, science, information technology and management optimization problems can be considered as non-linear programming real-world problems where all or some of the parameters and variables involved are uncertain in nature. These can only be quantified using intelligent computational techniques such as evolutionary computation and fuzzy logic. The main objective of this research paper is to solve non-linear fuzzy optimization problem where the technological coefficient in the constraints involved are fuzzy numbers, which was represented by logistic membership functions using the hybrid evolutionary optimization approach. To explore the applicability of the present study, a numerical example is considered to determine the production planning for the decision variables and profit of the company.
机译:许多工程,科学,信息技术和管理优化问题都可以视为非线性编程实际问题,其中涉及的所有或某些参数和变量本质上不确定。这些只能使用智能计算技术(例如进化计算和模糊逻辑)进行量化。本研究的主要目的是解决非线性模糊优化问题,其中涉及的约束中的技术系数是模糊数,这是使用混合进化优化方法由逻辑隶属函数表示的。为了探索本研究的适用性,考虑了一个数值示例来确定决策变量和公司利润的生产计划。

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