Particle swarm evolutionary computation-based framework for optimizing the risk and cost of low-demand systems of nuclear power plants-Reference-Cited by-同舟云学术

Particle swarm evolutionary computation-based framework for optimizing the risk and cost of low-demand systems of nuclear power plants

Published:2017-10-03 Issue:1 Volume:55 Page:19-28
ISSN:0022-3131
Container-title:Journal of Nuclear Science and Technology
language:en
Short-container-title:Journal of Nuclear Science and Technology

Author:

Ge Daochuan¹²,Chen Shanqi¹,Wang Zhen¹,Yang Yanhua²

Affiliation:

1. Key Laboratory of Neutronics and Radiation Safety, Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei 230031, Anhui, China

2. School of Nuclear Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Funder

National Science and Technology Major Project

Staff Independent Innovation Fund of State Nuclear Technology Corporation

National Natural Science Foundation

Publisher

Informa UK Limited

Subject

Nuclear Energy and Engineering,Nuclear and High Energy Physics

Link

https://www.tandfonline.com/doi/pdf/10.1080/00223131.2017.1383208

Reference32 articles.

1. Optimization of test and maintenance intervals based on risk and cost

2. A model for preventive maintenance planning by genetic algorithms based in cost and reliability

3. Safety management in NPPs using an evolutionary algorithm technique

4. The price of risk reduction: Optimization of test and maintenance integrating risk and cost

5. Multiobjective optimization of the inspection intervals of a nuclear safety system: A clustering-based framework for reducing the Pareto Front

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