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首页> 外文会议>ASME international design engineering technical conferences and computers and information in engineering conference 2011.;vol. 2 pt. A. >ENGINEERING SYSTEM DESIGN USING FIREFLY ALGORITHM AND MULTI-OBJECTIVE OPTIMIZATION
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ENGINEERING SYSTEM DESIGN USING FIREFLY ALGORITHM AND MULTI-OBJECTIVE OPTIMIZATION

机译：最优算法和多目标优化的工程系统设计

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摘要

Modern engineering problems, such as aircraft or automobile design, are often composed by a large number of variables that must be chosen simultaneously for better design performance. Normally, most of these parameters are conflicting, i.e., an improvement in one of them does not lead, necessarily, to better results for the other ones. Thus, many methods to solve multi-objective optimization problems (MOP) have been proposed. The MOP solution, unlike the single objective problems, is a set of non-dominated solutions that form the Pareto Curve, also known as Pareto Optimal. Among the MOP algorithms, we can cite the Firefly Algorithm (FA). FA is a bio-inspired method that mimics the patterns of short and rhythmic flashes emitted by fireflies in order to attract other individuals to their vicinities. For illustration purposes, in the present contribution the FA, associated with the Pareto dominance criterion, is applied to three different design cases. The first one is related to the geometric design of a clamped-free beam. The second one deals with the project of a welded beam and the last one focuses on estimating the characteristic parameters of a rotary dryer pilot plant. The proposed methodology is compared with other evolutionary strategies. The results indicate that the proposed approach characterizes an interesting alternative for multi-objective optimization problems.
机译：现代工程问题（例如飞机或汽车设计）通常由大量变量组成，必须同时选择这些变量才能获得更好的设计性能。通常，这些参数中的大多数是冲突的，即，其中一个参数的改进不一定会为其他参数带来更好的结果。因此，已经提出了许多解决多目标优化问题（MOP）的方法。与单目标问题不同，MOP解决方案是一组非支配的解决方案，这些解决方案构成了Pareto曲线，也称为Pareto最优。在MOP算法中，我们可以引用Firefly算法（FA）。 FA是一种受生物启发的方法，它模仿萤火虫发出的短促和有节奏的闪光的模式，以吸引其他人靠近他们。出于说明目的，在本文稿中，将与帕累托优势标准关联的FA应用于三个不同的设计案例。第一个涉及免夹紧梁的几何设计。第二个项目涉及焊接梁的项目，最后一个项目着重于估计旋转干燥机中试设备的特征参数。所提出的方法与其他进化策略进行了比较。结果表明，提出的方法是多目标优化问题的一个有趣的替代特征。

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