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Article
Publication date: 3 January 2017

A modified quantum-based particle swarm optimization for engineering inverse problem

Obaid Ur Rehman, Shiyou Yang and Shafi Ullah Khan

The purpose of this paper is to explore the potential of standard quantum-based particle swarm optimization (QPSO) methods for solving electromagnetic inverse problems.

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Abstract

Purpose

The purpose of this paper is to explore the potential of standard quantum-based particle swarm optimization (QPSO) methods for solving electromagnetic inverse problems.

Design/methodology/approach

A modified QPSO algorithm is designed.

Findings

The modified QPSO algorithm is an efficient and robust global optimizer for optimizing electromagnetic inverse problems. More specially, the experimental results as reported on different case studies demonstrate that the proposed method can find better final optimal solution at an early stage of the iterating process (uses less iterations) as compared to other tested optimal algorithms.

Originality/value

The modifications include the design of a new position updating formula, the introduction of a new mutation strategy and a dynamic control parameter to intensify the convergence speed of the algorithm.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 36 no. 1
Type: Research Article
DOI: https://doi.org/10.1108/COMPEL-02-2016-0042
ISSN: 0332-1649

Keywords

  • Inverse problem
  • Particle swarm optimization
  • Global optimization
  • Quantum mechanics

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Article
Publication date: 2 January 2018

An improved quantum based particle swarm optimizer applied to electromagnetic optimization problems

Obaid Ur Rehman, Shiyou Yang and Shafiullah Khan

The aim of this paper is to explore the potential of standard quantum particle swarm optimization algorithms to solve single objective electromagnetic optimization problems.

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Abstract

Purpose

The aim of this paper is to explore the potential of standard quantum particle swarm optimization algorithms to solve single objective electromagnetic optimization problems.

Design/methodology/approach

A modified quantum particle swarm optimization (MQPSO) algorithm is designed.

Findings

The MQPSO algorithm is an efficient and robust global optimizer for optimizing electromagnetic design problems. The numerical results as reported have demonstrated that the proposed approach can find better final optimal solution at an initial stage of the iterating process as compared to other tested stochastic methods. It also demonstrates that the proposed method can produce better outcomes by using almost the same computation cost (number of iterations). Thus, the merits or advantages of the proposed MQPSO method in terms of both solution quality (objective function values) and convergence speed (number of iterations) are validated.

Originality/value

The improvements include the design of a new position updating formula, the introduction of a new selection method (tournament selection strategy) and the proposal of an updating parameter rule.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 1
Type: Research Article
DOI: https://doi.org/10.1108/COMPEL-04-2017-0160
ISSN: 0332-1649

Keywords

  • Electromagnetic optimization
  • Particle swarm optimizer
  • Quantum mechanics
  • Tournament selection

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Article
Publication date: 30 November 2020

Design optimization of metamaterial units using a genetic algorithm based optimization methodology

Yiying Li and Shiyou Yang

The purpose of this paper is to develop a pertinent design optimization methodology for symmetric designs of a metamaterial (MM) unit.

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Abstract

Purpose

The purpose of this paper is to develop a pertinent design optimization methodology for symmetric designs of a metamaterial (MM) unit.

Design/methodology/approach

A cell division mechanism is introduced and used to design a new selecting mechanism in the proposed algorithm, a non-dominated sorting cellular genetic algorithm (NSCGA).

Findings

The numerical results on solving standard multi-objective test functions and a prototype MM unit positively demonstrate the advantages of the proposed NSCGA.

Originality/value

A new NSGAII-based optimization algorithm, NSCGA, for multi-objective optimization designs of a MM unit is proposed.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. ahead-of-print no. ahead-of-print
Type: Research Article
DOI: https://doi.org/10.1108/COMPEL-03-2020-0107
ISSN: 0332-1649

Keywords

  • Pareto front
  • Multi-objective optimization
  • Metamaterials
  • NSGAII

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Article
Publication date: 6 November 2017

A numerical method for solving the physics-based model of IGBT with all free-carrier injection conditions in the base region

Jiajia Chen, Yuhan Ma and Shiyou Yang

The purpose of this paper is to provide an accurate model and method to simulate the transient performances of an insulated gate bipolar transistor (IGBT) in an arbitrary…

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Abstract

Purpose

The purpose of this paper is to provide an accurate model and method to simulate the transient performances of an insulated gate bipolar transistor (IGBT) in an arbitrary free-carrier injection condition.

Design/methodology/approach

A numerical model and method for solving the physics-based model, an ambipolar diffusion equation-based model, of an IGBT is proposed.

Findings

The results of the proposed model are very close to the tested ones.

Originality/value

A mathematical model for an IGBT considering all free-carrier injection conditions is introduced, and a numerical solution methodology is proposed.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 36 no. 6
Type: Research Article
DOI: https://doi.org/10.1108/COMPEL-12-2016-0558
ISSN: 0332-1649

Keywords

  • Ambipolar diffusion equation
  • Insulated gate bipolar transistor
  • Physics-based model
  • Transient behaviour

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Article
Publication date: 2 January 2018

A dynamic particle swarm optimization method applied to global optimizations of engineering inverse problem

Shafiullah Khan, Shiyou Yang and Obaid Ur Rehman

The aim of this paper is to explore the potential of particle swarm optimization (PSO) algorithm to solve an electromagnetic inverse problem.

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Abstract

Purpose

The aim of this paper is to explore the potential of particle swarm optimization (PSO) algorithm to solve an electromagnetic inverse problem.

Design/methodology/approach

A modified PSO algorithm is designed.

Findings

The modified PSO algorithm is a more stable, robust and efficient global optimizer for solving the well-known benchmark optimization problems. The new mutation approach preserves the diversity of the population, whereas the proposed dynamic and adaptive parameters maintain a good balance between the exploration and exploitation searches. The numerically experimental results of two case studies demonstrate the merits of the proposed algorithm.

Originality/value

Some improvements, such as the design of a new global mutation mechanism and introducing a novel strategy for learning and control parameters, are proposed.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 1
Type: Research Article
DOI: https://doi.org/10.1108/COMPEL-08-2016-0352
ISSN: 0332-1649

Keywords

  • Optimization techniques
  • Algorithms
  • Particle swarm optimization
  • Global optimization
  • Inverse problems
  • Dynamic inertia weight
  • Mutation operator
  • Search process

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Article
Publication date: 1 January 2014

Studies on numerical methodologies for inverse problems and optimizations in China

Shiyou Yang, S.L. Ho, Yingying Yao, Lei Liu and Lie Wu

– The purpose of this paper is to explore the potential challenges in developing numerical methodologies for inverse problems and optimizations.

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Abstract

Purpose

The purpose of this paper is to explore the potential challenges in developing numerical methodologies for inverse problems and optimizations.

Design/methodology/approach

Summarizing previous research results mainly contributed by two research groups of Zhejiang University and Hong Kong Polytechnic University.

Findings

Computational intelligence plays an essential role in studying inverse problems and optimizations.

Originality/value

An up-to-date review on the current status of numerical methodologies, especially computational intelligences, for inverse problems and optimizations contributed by Chinese researchers.

Details

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 33 no. 1/2
Type: Research Article
DOI: https://doi.org/10.1108/COMPEL-11-2012-0335
ISSN: 0332-1649

Keywords

  • Evolutionary algorithm
  • Design optimization
  • Inverse problems
  • Numerical methodology

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Article
Publication date: 7 March 2016

3D eddy current and temperature field analysis of edge induction heater

Yilun Li and Shiyou Yang

The temperature drop, especially in the edge of rolled steel in the hot rolling cooling has a catastrophic effect on the steel quality. The purpose of this paper is to…

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Abstract

Purpose

The temperature drop, especially in the edge of rolled steel in the hot rolling cooling has a catastrophic effect on the steel quality. The purpose of this paper is to study the coupled eddy current-temperature field of a C-type edge induction heater to provide references for engineering applications and designs.

Design/methodology/approach

Three-dimensional finite element analysis (FEA) model of a C-type edge induction heater is developed. Especially, a numerical methodology to couple the eddy current and temperature fields is proposed for coupled eddy current and temperature problems involving movement components. FEA software ANSYS is used to solve the coupled eddy current and temperature fields. The heat loss from the eddy current fields is abstracted and processed, and taken as internal heat source in the analysis of the temperature field. The temperature distribution of the rolling steel is obtained.

Findings

The numerical results can predict exactly the temperature rise of the rolled steel by means of the edge induction heating system.

Practical implications

The proposed numerical methodology for coupling eddy current and temperature fields can be applied to engineering coupled eddy current and temperature problems involving movement components. Also, the developed model and method can be used in the analysis and design of the edge induction heating system.

Originality/value

A numerical methodology to couple eddy current and temperature field for solving multi-physics field problems involving movement components is proposed and implemented in available commercial software. A three-dimensional model of the C-type edge induction heat heater is developed. Finite element method is employed to study the coupled eddy current-thermal problem. A method to deal with the movement of the strip steel is proposed. The proposed methodology can be applied to other coupled eddy current-temperature field problem with moving components.

Details

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 35 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/COMPEL-04-2015-0152
ISSN: 0332-1649

Keywords

  • Induction heating
  • FE method
  • Eddy current loss
  • Coupled problem

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Article
Publication date: 1 December 2002

Developments of an efficient global optimal design technique – a combined approach of MLS and SA algorithm

S.L. Ho, Shiyou Yang, Peihong Ni and H.C. Wong

A new response surface model (RSM), the moving least squares (MLS) approximation, is proposed for reconstructing the objective/constraint functions for the design…

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Abstract

A new response surface model (RSM), the moving least squares (MLS) approximation, is proposed for reconstructing the objective/constraint functions for the design optimization of electromagnetic devices. The reconstructed functions are then combined with the simulated annealing (SA) algorithm to develop a computationally efficient technique to obtain the global solutions. The new method has: the “intelligence” to arrange the sample points, i.e. intensify the sample points in regions where a local optimum is likely to exist; the flexibility in dealing with irregular sample points; the self‐adaptive ability to regulate the parameters of the MLS models. Detailed numerical examples are given to validate the proposed technique.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 21 no. 4
Type: Research Article
DOI: https://doi.org/10.1108/03321640210437851
ISSN: 0332-1649

Keywords

  • Surfaces
  • Model
  • Simulation
  • Algorithms
  • Optimization

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Article
Publication date: 1 January 2014

Minimizing sidelobe levels and facilitating null placements of nonlinear antenna arrays using an improved particle swarm optimization method

Huijun Deng, Xue Li, Libao Sun and Shiyou Yang

The aim of this paper is to explore the potential of particle swarm optimization (PSO) methods for minimizing the sidelobe levels (SLL) and placing null at arbitrary…

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Abstract

Purpose

The aim of this paper is to explore the potential of particle swarm optimization (PSO) methods for minimizing the sidelobe levels (SLL) and placing null at arbitrary angles of a nonlinear antenna array.

Design/methodology/approach

An improved PSO algorithm is designed.

Findings

The improved PSO method is an efficient and robust global optimizer for minimizing the SLL and placing null at arbitrary angles of a nonlinear antenna array.

Originality/value

Some improvements, such as the design of some new formulae for both position and velocity updating, the introduction of an age variable, and the devise of an intensification searches using the cross entropy method, are proposed.

Details

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 33 no. 1/2
Type: Research Article
DOI: https://doi.org/10.1108/COMPEL-11-2012-0334
ISSN: 0332-1649

Keywords

  • Antenna array
  • Global optimization
  • Null placement
  • Particle swarm optimization

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Article
Publication date: 1 January 1994

TRANSIENT SIMULATION OF PERMANENT MAGNET DC COMMUTATOR MOTORS USING THE FINITE ELEMENT APPROACH

M. Wing and J.F. Gieras

The transient performance of permanent magnet dc commutator motors has been simulated using a two dimensional finite element model. The simulations of start‐up…

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Abstract

The transient performance of permanent magnet dc commutator motors has been simulated using a two dimensional finite element model. The simulations of start‐up characteristics and braking conditions are concentrated on. The finite element approach in simulating transients of dc motors is discussed with a proposed solution to the problem A finite element solution that ignores the induced eddy current losses in the small volume rotor is shown as a quick solution that gives fair accuracy. The results are compared against experimental data obtained for a 370 W permanent magnet dc motor using a data acquisition system.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 13 no. 1
Type: Research Article
DOI: https://doi.org/10.1108/eb051855
ISSN: 0332-1649

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