What question did this study set out to answer?

To develop a multi-objective particle swarm optimization framework using multiple guiders and cross-space crowding distance to avoid local Pareto fronts in electromagnetic design problems.

January 31, 2012IEEE Transactions on Magnetics

Multi-Guider and Cross-Searching Approach in Multi-Objective Particle Swarm Optimization for Electromagnetic Problems

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Authors

MPMinh-Trien PhamVNU University of Science DZDiahai ZhangChungbuk National University CKChang Seop KohChungbuk National University

Discussion

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Implication

Computational evaluation demonstrates improved Pareto-front exploration in electromagnetic benchmarks, highlighting the benefit of dual-space crowding distance and multiple guiders.

Key Points

To develop a multi-objective particle swarm optimization framework using multiple guiders and cross-space crowding distance to avoid local Pareto fronts in electromagnetic design problems.
Incorporated multiple guiders to steer swarm particles toward the global Pareto-optimal front.
Applied mutation operators to both active swarm particles and external archive members to evade local optima.
Calculated crowding distance across both variable space and objective space, evaluating performance on the TEAM 22 benchmark with three and eight design variables.
The multi-guider framework improved swarm convergence toward the Pareto front relative to conventional single-guider approaches.
Applying mutation to archive members and particles successfully prevented stagnation in local Pareto fronts.
Evaluating crowding distance across variable and objective spaces enhanced the diversity of non-dominated solutions across both 3-variable and 8-variable TEAM 22 test cases.

Cite This Study

Pham et al. (2012) studied this question.

synapsesocial.com/papers/6a816e598c6be3b56fc43ce5 https://doi.org/10.1109/tmag.2011.2173559

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January 31, 2012IEEE Transactions on Magnetics

Multi-Guider and Cross-Searching Approach in Multi-Objective Particle Swarm Optimization for Electromagnetic Problems

View Full Paper

Ask AI

Bookmark

Authors

MPMinh-Trien PhamVNU University of Science DZDiahai ZhangChungbuk National University CKChang Seop KohChungbuk National University

Discussion

Member takes

Implication

Computational evaluation demonstrates improved Pareto-front exploration in electromagnetic benchmarks, highlighting the benefit of dual-space crowding distance and multiple guiders.

Key Points

To develop a multi-objective particle swarm optimization framework using multiple guiders and cross-space crowding distance to avoid local Pareto fronts in electromagnetic design problems.
Incorporated multiple guiders to steer swarm particles toward the global Pareto-optimal front.
Applied mutation operators to both active swarm particles and external archive members to evade local optima.
Calculated crowding distance across both variable space and objective space, evaluating performance on the TEAM 22 benchmark with three and eight design variables.
The multi-guider framework improved swarm convergence toward the Pareto front relative to conventional single-guider approaches.
Applying mutation to archive members and particles successfully prevented stagnation in local Pareto fronts.
Evaluating crowding distance across variable and objective spaces enhanced the diversity of non-dominated solutions across both 3-variable and 8-variable TEAM 22 test cases.

Cite This Study

Pham et al. (2012) studied this question.

synapsesocial.com/papers/6a816e598c6be3b56fc43ce5 https://doi.org/10.1109/tmag.2011.2173559

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