烟花算法及其在多目标优化中的应用研究

烟花算法及其在多目标优化中的应用研究(论文14000字)
摘要：烟花算法（Fireworks Algorithm，FWA）是一种新型的群体智能算法，它在求解全局优化问题时展现出了优良的性能，近年来在业界也颇受关注。多目标优化是在各目标之间进行权衡并折中处理，使得各个目标函数达到最优值即pareto最优解集。论文主要研究烟花算法在多目标优化中的应用，分析二者相结合的优越性。通过查阅资料和深入学习，我清晰地认识到当前的探究状况和主要存在的不足。在烟花算法的研究基础上，通过和粒子群算法以及遗传算法的交叉对比，分析FWA在优化方面的稳定性和优越性。其次分析多目标优化算法的最优解问题即pareto最优解。最后测试多目标烟花算法的优化性能，并对测试结果进行分析与总结。通过对比几种多目标优化算法来分析和验证多目标烟花算法的性能，体现该算法的稳定性和优越性。目前，在用算法处理实际问题中，将烟花算法应用于多目标问题中所表现出的性能要优于其他优化算法。由此看来，在未来的发展历程中，多目标烟花算法在解决实际优化问题中或将得到广泛的运用。
关键词：烟花算法；多目标优化；Pareto最优解
 
Research on the Application of Fireworks Algorithm in Multiobjective Optimization [资料来源：https://www.doc163.com]
Abstract：Fireworks Algorithm is a new type of population intelligence algorithm. It has demonstrated excellent performance in solving global optimization problems and has received much attention in the industry in recent years. Multi-objective optimization is to balance and compromise between the goals, so that each objective function reaches the optimal value, that is, the pareto optimal solution set. This paper mainly studies the application of fireworks algorithm in multiobjective optimization and analyzes the advantages of combining them. Through my research and in-depth study, I clearly recognize the current state of inquiry and the major deficiencies. Based on the research of fireworks algorithm, the stability and superiority of FWA in optimization problem are analyzed by cross comparison with particle swarm algorithm and genetic algorithm. Secondly, the optimal solution of multiobjective optimization algorithm is analyzed. Finally, the optimization performance of the multi-target fireworks algorithm is tested, and the test results are analyzed and summarized. The performance of the multi-target fireworks algorithm is analyzed and verified by comparing several multi-objective optimization algorithms, which shows the stability and superiority of the algorithm. At present, the performance of the fireworks algorithm applied to multitarget problem is better than that of other optimization algorithms. From this point of view, in the future development process, multi-target fireworks algorithm may be widely used in solving practical optimization problems.

[资料来源：http://www.doc163.com]

目 录
1、绪论        1
1.1、研究背景与研究意义    1
1.2、研究现状    1
1.3、研究内容    2
1.4、论文结构    3
2、烟花算法    3
2.1、烟花算法工作流程    4
2.2、烟花算法算子分析    5
2.2.1、爆炸算子    5
2.2.2、变异算子    7
2.2.3、选择策略    7
2.4、与其他算法的比较    7
3、多目标优化    8
3.1、多目标优化概述    9
3.2、Pareto最优解    9
3.3、多目标优化算法模型    10
4、多目标烟花算法    11 [资料来源：https://www.doc163.com]
4.1、MOFWA适应度值计算    11
4.2、MOFWA进化策略    11
4.3、MOFWA测试函数    12
4.4、MOFWA算法流程    13
4.5、实验结果与分析    14
5、总结与展望    15
5.1、论文总结    15
5.2、研究展望    16
参考文献    17
致谢        19 [资料来源：www.doc163.com]