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Dependent-Chance Programming Models for Capital Budgeting in Fuzzy Environments 被引量:2
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作者 梁锐 高金伍 《Tsinghua Science and Technology》 SCIE EI CAS 2008年第1期117-120,共4页
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... 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. 展开更多
关键词 fuzzy variable capital budgeting dependent-chance programming genetic algorithm
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Optimization of PERT Network and Compression of Time
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作者 李平 胡建兵 顾新一 《Journal of Southwest Jiaotong University(English Edition)》 2005年第2期161-166,共6页
In the traditional methods of program evaluation and review technique (PERT) network optimization and compression of time limit for project, the uncertainty of free time difference and total time difference were not... In the traditional methods of program evaluation and review technique (PERT) network optimization and compression of time limit for project, the uncertainty of free time difference and total time difference were not considered as well as its time risk. The authors of this paper use the theory of dependent-chance programming to establish a new model about compression of time for project and multi-objective network optimization, which can overcome the shortages of traditional methods and realize the optimization of PERT network directly. By calculating an example with genetic algorithms, the following conclusions are drawn: ( 1 ) compression of time is restricted by cost ratio and completion probability of project; (2) activities with maximal standard difference of duration and minimal cost will be compressed in order of precedence; (3) there is no optimal solutions but noninferior solutions between chance and cost, and the most optimal node time depends on decision-maker's preference. 展开更多
关键词 Time compression for project Network optimization dependent-chance programming Genetic algorithms PERT network
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