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Dependent-chance programming models for capital budgeting in fuzzy environments

机译:模糊环境下资本预算的相依机会规划模型

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Capital budgeting is concerned with maximizing the total net profit subject to budget constraints by selecting an appropriate combination of projects. This paper presents chance maximizing models for capital budgeting with fuzzy input data and multiple conflicting objectives. When the decision maker sets a prospective profit level and wants to maximize the chances of the total profit achieving the prospective profit level, a fuzzy dependent-chance programming model, a fuzzy multi-objective dependent-chance programming model, and a fuzzy goal dependent-chance programming model are used to formulate the fuzzy capital budgeting problem. A fuzzy simulation based genetic algorithm is used to solve these models. Numerical examples are provided to illustrate the effectiveness of the simulation-based genetic algorithm and the potential applications of these models.
机译:资本预算涉及通过选择适当的项目组合来使总净利润最大化(受预算约束)。本文提出了具有模糊输入数据和多个冲突目标的资本预算机会最大化模型。当决策者设定预期利润水平并希望最大程度地提高总利润达到预期利润水平的机会时,请采用模糊相依机会规划模型,模糊多目标相依机会规划模型和模糊目标相依规划模型,用机会规划模型来表达模糊资本预算问题。基于模糊仿真的遗传算法用于求解这些模型。提供了数值示例,以说明基于仿真的遗传算法的有效性以及这些模型的潜在应用。

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