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基于可信性理论,提出一类新的带有模糊参数的风险投资机会约束模型。由于提出的风险投资问题包含带有无限支撑的模糊变量参数,因此它是一个无限维的优化问题。为了求解这个模糊优化问题,这里将逼近方法嵌套到神经网络和遗传算法中产生一个基于遗传算法的混合智能算法求解本文提出的带有模糊参数的风险投资机会约束问题。最后,给出一个数值例子来表明所设计模型和算法的实用性。
Based on the theory of credibility, a new type of opportunistic investment opportunity constraint model with fuzzy parameters is proposed. It is an infinite dimensional optimization problem because the proposed venture capital problem contains fuzzy parameters with infinite support. In order to solve this fuzzy optimization problem, a hybrid genetic algorithm-based hybrid intelligent algorithm is proposed to solve the problem of risk investment with fuzzy parameters in this paper by nesting approximation methods into neural networks and genetic algorithms. Finally, a numerical example is given to show the practicability of the proposed model and algorithm.