438
Views
4
CrossRef citations to date
0
Altmetric
Article

Loading pattern optimization for a PWR using Multi-Swarm Moth Flame Optimization Method with Predator

, ORCID Icon & ORCID Icon
Pages 523-536 | Received 17 Jun 2019, Accepted 17 Nov 2019, Published online: 17 Dec 2019

References

  • Wall I, Fenech H. The application of dynamic programming to fuel management optimization. Nucl Sci Eng. 1965;22:285–297.
  • Naft NB, Sesonske A. Pressurized water reactor optimal fuel management. Nucl Technol. 1971;14:123–132.
  • Stout BR Optimization of in-core nuclear fuel management in a pressurized water reactor [dissertation]. Corvallis(OR): Oregon State University at Oregon; 1973.
  • Terney BW, Williamson AE Jr. The design of reload cores using optimal control theory. Nucl Sci Eng. 1982;82:260–288.
  • Chao YA, Hu CW, Suo CA. A theory of fuel management via backward diffusion calculation. Nucl Sci Eng. 1986;93:78–87.
  • Downar. JT, Kim. JY. A reverse depletion method for pressurized water reactor core reload design. Nucl Sci Eng. 1986;93:78–87.
  • Stillman AJ, Chao AY, Downar JT. The Optimum fuel and power distribution for a pressurized water reactor burnup cycle. Nucl Sci Eng. 1989;103:321–333.
  • Parks TG. An intelligent stochastic optimization routine for nuclear fuel cycle design, nuclear technology. Nucl Technol. 1990;89:223–246.
  • Parks TG. Multiobjective pressurized water reactor reload core design by nondominated genetic algorithm search. Nucl Sci Eng. 1996;124:178–187.
  • Yamamoto A Study on advanced in-core fuel management for pressurized water reactors using loading pattern optimization methods [dissertation]. Kyoto: Kyoto University at Kyoto; 1998.
  • Meneses MAA. Particle swarm optimization applied to the nuclear reload problem of a pressurized water reactor. Prog Nucl Energy. 2009;51:319–326.
  • Safarzadeh A, Zolfaghari A, Norouzi A, et al. Loading pattern optimization of PWR reactors using artificial bee colony. Ann Nucl Energy. 2011;38:2218–2226.
  • Lin C, Lin FB. Automatic pressurized water reactor loading pattern design using ant colony algorithms. Ann Nucl Energy. 2012;43:91–98.
  • Mirjalili S. Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowledge-Based Syst. 2015;89:228–229.
  • Sayed IG, Hassanien EA. A hybrid SA-MFO algorithm for function optimization and engineering design problems. Complex Intell Syst. 2018;4:195–212.
  • Inukai N, Inoue T, Uwate Y, et al. Investigation of particle swarm optimization with predator. Tokyo: the institute of electronics, information and communication engineers; 2013. (Technical Report of IEICE; Report No. 113 p. 109–112).
  • Xia X, Gui L, Zhan Z. A multi-swarm particle swarm optimization algorithm based on dynamical topology and purposeful detecting. Appl Soft Comput. 2018;67:126–140.
  • Park KT, Lee CH, Foo KH, et al. Loading pattern optimization by multi-objective simulated annealing with screening technique. In: Proceedings of PHYSOR-2006;2006 Sep 10–14; Vancouver, BC, Canada. Vancouver (BC): The Canadian Nuclear Society; 2006.
  • Genshirosekkei OY. [Design of reacotor]. Tokyo: Ohmsha; 2010. Japanese. p. 113,156.
  • Chang CY, Sesonske A. Optimization and analysis of low-leakage core management for pressurized water reactors. Nucl Technol. 1984;65:292–304.
  • The R project for statistical computing [Internet]. Vienna(Austria): R Foundation for Statistical Computing; cited 2019 June 14]. Available from . https://www.R-project.org/

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.