基于混合粒子群优化的模糊规划求解新方法

2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007) Pub Date : 2007-12-15 DOI:10.1109/CIS.WORKSHOPS.2007.135

Zhenkui Pei, Shengfeng Tian, Houkuan Huang

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引用次数: 3

摘要

模糊规划为处理具有模糊参数的优化问题提供了一种强有力的手段。在过去，模糊规划以不同的方式被使用。粒子群算法已成功地应用于连续非线性约束优化问题、神经网络等。但在文献中尚未发现将粒子群算法应用于模糊规划。本文将模糊仿真、神经网络和粒子群算法相结合，提出了一种混合智能算法。在此基础上，介绍了求解模糊期望值模型的混合智能算法。算例说明了该算法的有效性和有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Novel Method for Solving Fuzzy Programming Based on Hybrid Particle Swarm Optimization

Fuzzy programming offers a powerful means of handling optimization problems with fuzzy parameters. Fuzzy programming has been used in different ways in the past. The particle swarm optimization (PSO) has been applied successfully to continuous nonlinear constrained optimization problems, neural network, etc. But we have not been found to use PSO for fuzzy programming in literature. In this paper, we combined with fuzzy simulation, neural network and PSO to produce a hybrid intelligent algorithm. Based on this hybrid intelligent algorithm, we introduced for solving fuzzy expected value models. Some numerical examples are given to illustrate the algorithm is effective and powerful.

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来源期刊

2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)

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