A comprehensive survey on particle swarm optimization algorithm and its applications
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
A review on optimization methods for nuclear reactor fuel reloading analysis
Z Li, J Wang, M Ding - Nuclear Engineering and Design, 2022 - Elsevier
Nuclear reactor fuel reloading optimization is a hot issue in the field of nuclear engineering.
With the reasonable rearrangement of fuel assemblies in a reactor core, the nuclear fuel …
With the reasonable rearrangement of fuel assemblies in a reactor core, the nuclear fuel …
Development and research of triangle-filter convolution neural network for fuel reloading optimization of block-type HTGRs
Z Li, J Wang, J Huang, M Ding - Applied Soft Computing, 2023 - Elsevier
The problem of fuel reloading optimization is very demanding, which requires to search for
the optimal suitable core configuration within a very huge solution space. To solve this …
the optimal suitable core configuration within a very huge solution space. To solve this …
A novel multi-swarm particle swarm optimization with dynamic learning strategy
In the paper, we proposed a novel multi-swarm particle swarm optimization with dynamic
learning strategy (PSO-DLS) to improve the performance of PSO. To promote information …
learning strategy (PSO-DLS) to improve the performance of PSO. To promote information …
Fractional-order particle swarm based multi-objective PWR core loading pattern optimization
In this study the multi-objective core reload pattern optimization has been performed using
the Fractional Order Particle Swarm Optimization (FOPSO) algorithm. The multi-objective …
the Fractional Order Particle Swarm Optimization (FOPSO) algorithm. The multi-objective …
A simplified multi-objective particle swarm optimization algorithm
Particle swarm optimization is a popular nature-inspired metaheuristic algorithm and has
been used extensively to solve single-and multi-objective optimization problems over the …
been used extensively to solve single-and multi-objective optimization problems over the …
The use of multi-objective optimization to improve the design process of nuclear power plant systems
PR Wilding, NR Murray, MJ Memmott - Annals of Nuclear Energy, 2020 - Elsevier
Multi-objective optimization is proposed to address the problem of design optimality in the
nuclear power plant design process. This is done via the creation/development of the …
nuclear power plant design process. This is done via the creation/development of the …
Energy management strategy of connected hybrid electric vehicles considering electricity and oil price fluctuations: A case study of ten typical cities in China
Energy management strategy (EMS) plays an important role in improving energy economy
of plug-in hybrid electric vehicles (PHEVs). The frequently fluctuations of electricity and oil …
of plug-in hybrid electric vehicles (PHEVs). The frequently fluctuations of electricity and oil …
Dynamic routing for waste collection and transportation with multi-compartment electric vehicle using smart waste bins
J Yang, F Tao, Y Zhong - Waste Management & Research, 2022 - journals.sagepub.com
The municipal solid waste (MSW) collection and transportation issue has been studied by
numerous researchers; however, a few studies consider the chance-constrained …
numerous researchers; however, a few studies consider the chance-constrained …
An innovative hybrid multi-objective particle swarm optimization with or without constraints handling
S Cheng, H Zhan, Z Shu - Applied Soft Computing, 2016 - Elsevier
This paper presents a new hybrid optimizer in which an innovative optimal particles local
search strategy on basis of bound optimization by quadratic approximation (BOBYQA) …
search strategy on basis of bound optimization by quadratic approximation (BOBYQA) …