Theory and Practice of Uncertain Programming
Theory and Practice of Uncertain Programming
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DOI：
10.1007/978-3-540-89484-1
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发表时间：
2003-04
期刊：
影响因子：
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通讯作者：
Baoding Liu
中科院分区：
文献类型：
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作者：
Baoding Liu
现实生活中的决策通常是在不确定的状态下做出的。我们如何在不确定的环境中对优化问题建模？我们如何解决这些模型？本书的主要目的就是提供不确定编程理论来回答这些问题。不确定规划是指不确定环境下的优化理论。随机规划、模糊规划和混合规划是不确定规划的子课题。这本书提供了一个独立的，全面的和最新的不确定规划理论的介绍，包括许多建模思想和应用在系统可靠性设计，项目调度问题，车辆路线问题，设施选址问题，和机器调度问题。许多智能算法如遗传算法和神经网络已经被不同背景的研究者开发出来。一个自然的想法是整合这些智能算法，以产生更有效和强大的算法。为了解决不确定的规划模型，在书中记录了一系列混合智能算法。作者还开设了自己的网站http://orsc。edu。cn/liu发布仿真、遗传算法、神经网络、混合智能算法的c++源文件。
Real-life decisions are usually made in the state of uncertainty. How do we model optimization problems in uncertain environments? How do we solve these models? The main purpose of the book is just to provide uncertain programming theory to answer these questions. By uncertain programming we mean the optimization theory in uncertain environments. Stochastic programming, fuzzy programming and hybrid programming are subtopics of uncertain programming. This book provides a self-contained, comprehensive and up-to-date presentation of uncertain programming theory, including numerous modeling ideas and applications in system reliability design, project scheduling problem, vehicle routing problem, facility location problem, and machine scheduling problem.Numerous intelligent algorithms such as genetic algorithms and neural networks have been developed by researchers of different backgrounds. A natural idea is to integrate these intelligent algorithms to produce more effective and powerful algorithms. In order to solve uncertain programming models, a spectrum of hybrid intelligent algorithms are documented in the book. The author also maintains a website at http://orsc. edu. cn/liu to post the C++ source files of simulations, genetic algorithms, neural networks, and hybrid intelligent algorithms.