Dependent-Chance Programming Models for Capital Budgeting in Fuzzy Environments |
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Authors: | Rui Liang, ,Jinwu Gao,
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Affiliation: | aEconomy, Industry and Business Management College, Chongqing University, Chongqing 400044, China;bSchool of Information, Renmin University of China, Beijing 100872, China |
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Abstract: | 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 prospec-tive 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 po-tential applications of these models. |
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Keywords: | fuzzy variable capital budgeting dependent-chance programming genetic algorithm |
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