A Novel Hybrid Multi-Objective Optimization Algorithm and Its Application to Designs of Electromagnetic Devices

In this article, a novel hybrid multi-objective optimization (MOO) algorithm is proposed by combining an improved sparrow search algorithm (SSA) with an improved non-dominated sorting genetic algorithm (NSGA-II). The original SSA is improved by the introduction of population updating mechanism of mo...

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Vydané v:IEEE transactions on magnetics Ročník 61; číslo 2; s. 1 - 4
Hlavní autori: Li, Yilun, Xie, Zhengwei, Yang, Shiyou, Ren, Zhuoxiang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.02.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Actuators
Adaptive algorithms
Adaptive sampling
Diversity reception
Electromagnetic devices
Evolutionary algorithms
Fires
Flowcharts
Genetic algorithms
Heuristic algorithms
Hypercubes
Latin hypercube sampling
multi-objective optimization (MOO)
Multiple objective analysis
Optimization
Polynomials
Search algorithms
Search problems
Sorting
Sorting algorithms
TEAM22 benchmark
Topology optimization
ISSN:0018-9464, 1941-0069
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Shrnutí:In this article, a novel hybrid multi-objective optimization (MOO) algorithm is proposed by combining an improved sparrow search algorithm (SSA) with an improved non-dominated sorting genetic algorithm (NSGA-II). The original SSA is improved by the introduction of population updating mechanism of moth-flame optimization (MFO) algorithm and by adopting adaptive mutation; meanwhile, NSGA-II is enhanced by using Latin hypercube sampling and dynamical selection mechanism of crossover and mutation operators. The performance of the proposed hybrid algorithm is verified using standard test functions and it is applied to the multi-objective optimal designs of TEAM22 benchmark problem and topology optimization problem of an electromagnetic actuator prototype. Numerical results demonstrate the effectiveness and superiority of the proposed algorithm.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2024.3519202