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arXiv · 2107.11201

A Fitness Landscape View on the Tuning of an Asynchronous Master-Worker EA for Nuclear Reactor Design

Mathieu Muniglia·Sébastien Verel·Jean-Charles Le Pallec·Jean-Michel Do
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Abstract

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.

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Mathieu Muniglia, Sébastien Verel, Jean-Charles Le Pallec, Jean-Michel Do. 2021-07-06. A Fitness Landscape View on the Tuning of an Asynchronous Master-Worker EA for Nuclear Reactor Design. https://doi.org/10.1007/978-3-319-78133-4_3

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