多目标粒子群算法原理及其应用分析

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1、-内蒙古科技大学硕士学位论文5.2甲醇合成模型的建立···························································································525.2.1甲醇合成数据选取·····················································································525.2.2煤制甲醇数学模型建立·························································

2、····················535.3算法应用················································································································585.4本章小结················································································································60结论·························

3、·········································································································62参考文献······························································································································63附录A多目标粒子群在MATLAB中程序·································

4、····································68在学研究成果······················································································································77致谢·····························································································································

5、·····78----3----内蒙古科技大学硕士学位论文1绪论5.2多目标优化问题研究背景及现状优化问题意思是在满足指定条件下，尽可能的找出一种方法、策略亦或是一类参数值，使得所要求解的目标问题达到最优最好，所研究的内容是在众多方案中如何找到最佳的解决方案的思考方法。优化问题已经被大范围地应用在国防、军事、钢铁、交通、建筑、材料、通信等许多领域范围。对于优化方法，这是一类以数学为根基，目的用来解决各类多目标优化问题的实用科技。许多国家科技专家都非常重视并开始研究优化问题的理论和技术，通过各种研究创新，目前应用优化方法的各种领域，已经正在或者开始产生了巨大的经济利益和社会价值

6、。经过多次实践验证，经过优化方法处理的工艺技术，能够有效的提高工作效率、降低能源消耗、资源能够合理利用，随着优化方法的进一步研究及其生产规模的进一步扩大，这种合理归置工艺技术的效果也会更加明显。在管理学、金融学、、交通运输、计算机应用科学、国防建设等学科及其诸多应用优化方法的领域中，经常出现许多复杂的、难以单方面解决的多目标优化问题。面对这些复杂的、困难的优化问题，尽管许多传统的优化方法，诸如牛顿寻优法、共扼梯度法和单纯形法等都能够搜索整个寻优空间，但是这些传统的方法无法在复杂条件下完成搜索，极度轻易就会发生搜索过程中的组合爆炸。考虑到工作问题中的许多现实特点，例如诸多条件约

7、束、函数方程的非线性、现实中的复杂性以及生产工艺难以建模等困难，要解决上述困难，优化算法迫切呼吁寻求更加高效的寻优方法，这成为相关学科的主要研究内容之一。群智能优化算法(SwarmIntelligenceOptimization)是一种典型的人工智能算法，该方法是通过对自然界中生物的群体迁徙、群体觅食等一系列大规模生物活动，生物学家通过其表现出来的社会行为进行观察及研究发现，群居式的生物群体可以被当作一个整体式系统，该系统组织严谨，活动规律，一般呈现出整体规模的有规律活动，尽管在整个系统中的个体都非常简