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首页> 外文期刊>International journal of numerical modelling >A multi-objective optimization algorithm based on self-organizing maps applied to wireless power transfer systems
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A multi-objective optimization algorithm based on self-organizing maps applied to wireless power transfer systems

机译：基于自组织映射的多目标优化算法在无线电力传输系统中的应用

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In this work, a new multi-objective population-based optimization algorithm is presented and tested. In this contribution, the concepts of fast non-dominating sorting and density estimation using the crowding distance are used to create a multi-objective optimization algorithm based on previous work, which is a single objective evolutionary optimization algorithm based on self-organizing maps (SOMs). The SOMs paradigm introduces a strong collaboration between neighbors solutions that improves exploitation. Furthermore, the representative power of the SOMs enhances the exploration and diversification. A state of the art benchmark approach is used to evaluate the performance of the proposed algorithm, obtaining positive results. The test problem uses an analytical model of an inductively coupled wireless power transfer system (WPT). The objective is to optimize the WPT model characteristics in order to allow simultaneous data and power transfer between the coils. The WPT design approach uses more degrees of freedom than existing techniques leading to a number of solutions where both the power signals and the data signal can coexist on the same physical channel achieving good figures of merit. Copyright (c) 2016 John Wiley & Sons, Ltd.
机译：在这项工作中，提出并测试了一种新的基于多目标总体的优化算法。在这项贡献中，使用拥挤距离进行快速非支配排序和密度估计的概念被用于创建基于先前工作的多目标优化算法，该算法是基于自组织映射（SOM）的单目标进化优化算法）。 SOM范例在邻居解决方案之间引入了强大的协作，从而提高了开发效率。此外，SOM的代表性力量增强了探索和多元化。最新的基准测试方法用于评估所提出算法的性能，从而获得积极的结果。测试问题使用电感耦合无线功率传输系统（WPT）的分析模型。目的是优化WPT模型特性，以允许线圈之间同时进行数据和功率传输。与现有技术相比，WPT设计方法使用了更多的自由度，从而导致了许多解决方案，其中功率信号和数据信号可以共存于同一物理信道上，从而获得良好的品质因数。版权所有（c）2016 John Wiley＆Sons，Ltd.

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