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A genetic algorithm for capital budgeting problem with fuzzy parameters

机译:模糊参数资本预算问题的遗传算法

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When an organization utilizes modern technology in its manufacturing process, it needs to update and upgrade its facilities repetitively by efficient ways to stay with great productivity along with efficiency so. Capital Budgeting (CB) problem is one of the most important issues in decision makings about capital in the manufacturing management. Sometimes all variables and parameters are not necessarily deterministic and enough experiments are not available. Current study develops a chance constrained integer programming in the fuzzy environment for capital budgeting. Considering the complexity theory, a good answer could not be found in reasonable time, so that an intelligent Genetic Algorithm (GA) as a metaheuristic approach is provided to trace this problem with satisfying solutions. Thereupon, a fuzzy simulation-based genetic algorithm is provided for solving chance constrained integer programming model with fuzzy parameters.
机译:当一个组织在其制造过程中利用现代技术时,它需要通过高效的方式重复地更新和升级其设施,以便保持良好的生产力以及效率。资本预算(CB)问题是关于制造管理中资本决策的最重要问题之一。有时,所有变量和参数都不一定是确定性的,并且不提供足够的实验。目前的研究在模糊环境中开发了一个机会限制了资本预算中的模糊环境。考虑到复杂性理论,在合理的时间内找不到一个很好的答案,从而提供了一种智能遗传算法(GA)作为一种成群质方法,以跟踪满足解决方案。于是,提供了一种模糊仿真的遗传算法,用于解决与模糊参数的机会约束整数编程模型。

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