Fuzzy random chance-constrained programming
Fuzzy random chance-constrained programming
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DOI：
10.1109/91.963757
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发表时间：
2001-10-01
影响因子：
11.9
通讯作者：
Liu, BD
中科院分区：
文献类型：
--
作者：
Liu, BD
所谓模糊随机规划，是指处理模糊随机决策问题的最优化理论。本文提出了模糊随机事件机会的新概念，并在此基础上构造了模糊随机机会约束规划的一般框架。我们还设计了一系列模糊随机模拟来计算模糊随机规划领域中出现的不确定函数。为了加快处理不确定函数的速度，基于模糊随机模拟产生的训练数据，训练神经网络逼近不确定函数。最后，将模糊随机模拟、神经网络和遗传算法相结合，提出了一种求解模糊随机规划模型的更强大、更有效的混合智能算法，并通过数值算例说明了该算法的有效性。
By fuzzy random programming, we mean the optimization theory dealing with fuzzy random decision problems. This paper presents a new concept of chance of fuzzy random events and then constructs a general framework of fuzzy random chance-constrained programming (CCP). We also design a spectrum of fuzzy random simulations for computing uncertain functions arising in the area of fuzzy random programming. To speed up the process of handling uncertain functions, we train a neural network to approximate uncertain functions based on the training data generated by fuzzy random simulation. Finally, we integrate fuzzy random simulation, neural network, and genetic algorithm to produce a more powerful and effective hybrid intelligent algorithm for solving fuzzy random programming models and illustrate its effectiveness by some numerical examples.