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## Hybrid genetic algorithm for electromagnetic topology optimization (2003)

Venue: | IEEE Trans. Magn |

Citations: | 5 - 1 self |

### Citations

407 | How learning can guide evolution
- Hinton, Nowlan
- 1987
(Show Context)
Citation Context ...optimizations, and the local optimizations are only used as a fitness evaluation. Generally, the Lamarckian GAs have been more widely accepted and the Baldwinian GAs’ use has been somewhat restricted =-=[15]-=-, [16]. In this paper, we adopted the concepts of the Lamarckian GAs. The proposed local optimization algorithm requires many function calls and consumes extensive computational time. Fig. 4. An examp... |

262 | Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach
- Dale, Sereno
- 1993
(Show Context)
Citation Context ...Reconstructing electric activity inside a brain using magnetic measurements outside the head has attracted a great deal of interest and is usually referred to as the MEG source reconstruction problem =-=[17]-=-, [18]. A simplified MEG model was selected for the verification of the optimization algorithm. Fig. 6 shows the schematic view of the simulation model. Sixteen -directional superconducting quantum in... |

86 | Lamarckian evolution, the Baldwin effect and function optimization
- Whitley, Gordon, et al.
- 1994
(Show Context)
Citation Context ...zations, and the local optimizations are only used as a fitness evaluation. Generally, the Lamarckian GAs have been more widely accepted and the Baldwinian GAs’ use has been somewhat restricted [15], =-=[16]-=-. In this paper, we adopted the concepts of the Lamarckian GAs. The proposed local optimization algorithm requires many function calls and consumes extensive computational time. Fig. 4. An example to ... |

74 |
Genetic placement
- Cohoon, Paris
- 1987
(Show Context)
Citation Context ...acteristic that stems from the derivatives of the objective functions. In this paper, a hybrid GA for electromagnetic topology optimization is proposed. The GA adopts a two-dimensional (2-D) encoding =-=[9]-=- to represent the geometrical topology effectively. A multidimensional geographic crossover is applied to increase the diversity of the population [10]–[12]. The effectiveness of this approach has alr... |

16 |
On multi-dimensional encoding/crossover
- Bui, Moon
- 1995
(Show Context)
Citation Context ...d. The GA adopts a two-dimensional (2-D) encoding [9] to represent the geometrical topology effectively. A multidimensional geographic crossover is applied to increase the diversity of the population =-=[10]-=-–[12]. The effectiveness of this approach has already been verified through its application to computer science [10], [11] and very large scale integration (VLSI) circuit design [12]. However, its app... |

11 |
A Two-Dimensional Genetic Algorithm for the Ising Problem
- Anderson, Jones, et al.
- 1991
(Show Context)
Citation Context ...ock-uniform crossover on a 2-D matrix chromosome that tessellated the chromosome into blocks; for each block, the genes in the block are copied from a uniformly selected parent, as shown in Fig. 2(b) =-=[14]-=-. It is evident that the block uniform crossover has a greater opportunity to generate more diverse offspring. Most recently, Bui and Moon proposed a geographic crossover to increase the diversity of ... |

7 |
A two-dimensional embedding of graphs for genetic algorithms
- Moon, Kim
- 1997
(Show Context)
Citation Context ...l geographic crossover is applied to increase the diversity of the population [10]–[12]. The effectiveness of this approach has already been verified through its application to computer science [10], =-=[11]-=- and very large scale integration (VLSI) circuit design [12]. However, its application to topology optimization is totally new, not only in electromagnetic optimizations, but also in mechanical ones. ... |

6 |
Niching genetic algorithm adopting restricted competition selection combined with pattern search method
- Kim, Cho, et al.
- 2002
(Show Context)
Citation Context ...TION STOCHASTIC optimization algorithms have been widelyused for various electromagnetic optimization problems, in particular to optimize the geometrical dimensions of various electromagnetic devices =-=[1]-=-–[4]. The genetic algorithm (GA), simulated annealing (SA), evolution strategy (ES), and tabu search algorithm, etc. are all well-known examples of the stochastic algorithms. Unfortunately, they have ... |

6 |
GEORG: VLSI circuit partitioner with a new genetic algorithm framework
- Moon, Lee, et al.
- 1998
(Show Context)
Citation Context ...e GA adopts a two-dimensional (2-D) encoding [9] to represent the geometrical topology effectively. A multidimensional geographic crossover is applied to increase the diversity of the population [10]–=-=[12]-=-. The effectiveness of this approach has already been verified through its application to computer science [10], [11] and very large scale integration (VLSI) circuit design [12]. However, its applicat... |

5 | A multiresolution framework to MEG/EEG source imaging
- Gavit, Baillet, et al.
- 2001
(Show Context)
Citation Context ...tructing electric activity inside a brain using magnetic measurements outside the head has attracted a great deal of interest and is usually referred to as the MEG source reconstruction problem [17], =-=[18]-=-. A simplified MEG model was selected for the verification of the optimization algorithm. Fig. 6 shows the schematic view of the simulation model. Sixteen -directional superconducting quantum interfer... |

4 |
Topology optimization of electrical devices using mutual energy and sensitivity
- Byun, Hahn
- 1999
(Show Context)
Citation Context ...ficulty in dealing with large numbers of design variables. Instead, sensitivity analysis has attracted much interest because it can deal with large amounts of design variables quickly and effectively =-=[6]-=-–[8]. However, it has the problem that a solution may converge on a local minimum, due to its natural deterministic characteristic that stems from the derivatives of the objective functions. In this p... |

3 | Optimization of Coil Shape in Deflection Yoke Considering Practical Coil Winding - Im, Kim, et al. |

3 |
An improved tabu search for the global optimizations of electromagnetic devices
- Ho, Shiyou
- 2001
(Show Context)
Citation Context ... STOCHASTIC optimization algorithms have been widelyused for various electromagnetic optimization problems, in particular to optimize the geometrical dimensions of various electromagnetic devices [1]–=-=[4]-=-. The genetic algorithm (GA), simulated annealing (SA), evolution strategy (ES), and tabu search algorithm, etc. are all well-known examples of the stochastic algorithms. Unfortunately, they have not ... |

3 | Inverse problem application of topology optimization method with mutual energy concept and design sensitivity - Byun, Lee, et al. - 2000 |

3 |
Topology optimization of electrostatic actuator using design sensitivity
- Byun, Park, et al.
(Show Context)
Citation Context ...lty in dealing with large numbers of design variables. Instead, sensitivity analysis has attracted much interest because it can deal with large amounts of design variables quickly and effectively [6]–=-=[8]-=-. However, it has the problem that a solution may converge on a local minimum, due to its natural deterministic characteristic that stems from the derivatives of the objective functions. In this paper... |

3 |
A comparison of MRI magnet design using a hopfield network and the optimized material distribution method
- Lowther, Mai, et al.
- 1998
(Show Context)
Citation Context ...local optimization can be easily confirmed. B. Case Study II—Source Optimization Problem Magnetic resonance imaging (MRI) coil design is a typical application of the source optimization problem [19], =-=[20]-=-. Fig. 10 shows the numerical model under consideration and the initial magnetic field distribution. The problem was to make the -directional flux density in a measuring box constant. A 12 14 (totalin... |

2 |
Optimal core shape design for cogging torque reduction of brushless DC motor using genetic algorithm
- Han, Cho, et al.
- 2000
(Show Context)
Citation Context ...and tabu search algorithm, etc. are all well-known examples of the stochastic algorithms. Unfortunately, they have not been applied much to direct shape optimization or topology optimization problems =-=[5]-=-, because they carry a severe computational cost and have difficulty in dealing with large numbers of design variables. Instead, sensitivity analysis has attracted much interest because it can deal wi... |

2 |
Faster calculation of sensitivity in the source current distribution problem using reciprocity theorem
- Lee, Byun, et al.
- 2001
(Show Context)
Citation Context ... with local optimization can be easily confirmed. B. Case Study II—Source Optimization Problem Magnetic resonance imaging (MRI) coil design is a typical application of the source optimization problem =-=[19]-=-, [20]. Fig. 10 shows the numerical model under consideration and the initial magnetic field distribution. The problem was to make the -directional flux density in a measuring box constant. A 12 14 (t... |

1 | A self-learning simulated annealing algorithm for global optimizations of electromagnetic devices - Yang, Machado, et al. - 2000 |