用于核反应堆设计的异步主-工人程序EA调试的适应性前景
A Fitness Landscape View on the Tuning of an Asynchronous Master-Worker EA for Nuclear Reactor Design
摘要：
在引入间歇性可再生能源的背景下，我们建议优化核电厂控制棒的主要变量，以提高其负载跟踪能力。设计问题是一个黑箱组合优化问题，具有昂贵的评估的基础上的多物理场模拟器。因此，我们使用并行异步主从进化算法扩展到千计算单元。一个主要问题是算法参数的调整。对这个昂贵的现实问题进行了适应度景观分析，表明可以根据适应度景观特征的低成本估计来调整变异参数。
英文摘要：
In the context of the introduction of intermittent renewable energies, we propose to optimize the main variables of the control rods of a nuclear power plant to improve its capability to load-follow. The design problem is a black-box combinatorial optimization problem with expensive evaluation based on a multi-physics simulator. Therefore, we use a parallel asynchronous master-worker Evolutionary Algorithm scaling up to thousand computing units. One main issue is the tuning of the algorithm parameters. A fitness landscape analysis is conducted on this expensive real-world problem to show that it would be possible to tune the mutation parameters according to the low-cost estimation of the fitness landscape features.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
