Chance-constrained programming models for capital budgeting with NPV as fuzzy parameters

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摘要

In an uncertain economic environment, experts’ knowledge about outlays and cash inflows of available projects consists of much vagueness instead of randomness. Investment outlays and annual net cash flows of a project are usually predicted by using experts’ knowledge. Fuzzy variables can overcome the difficulties in predicting these parameters. In this paper, capital budgeting problem with fuzzy investment outlays and fuzzy annual net cash flows is studied based on credibility measure. Net present value (NPV) method is employed, and two fuzzy chance-constrained programming models for capital budgeting problem are provided. A fuzzy simulation-based genetic algorithm is provided for solving the proposed model problems. Two numerical examples are also presented to illustrate the modelling idea and the effectiveness of the proposed algorithm.

论文关键词:Capital budgeting,Fuzzy programming,Chance-constrained programming,NPV

论文评审过程:Received 7 November 2005, Revised 19 November 2005, Available online 18 January 2006.

论文官网地址:https://doi.org/10.1016/j.cam.2005.11.026