Neighborhood Strategies for QPSO Algorithms to Solve Benchmark Electromagnetic Problems

Duca, Anton; Duca, Laurentiu; Ciuprina, Gabriela; Dumitrache, Ioan

doi:10.5220/0006040901480155

Cited by 9 publications

(4 citation statements)

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“…To test the proposed approach two electromagnetic optimization problems were chosen, namely TEAM 22 [17] and Loney's solenoid [18]. The implementation details of the TEAM 22 and Loney's solenoid benchmarks are the same as in the previous papers [8] [19].…”

Section: Resultsmentioning

confidence: 99%

“…where The evaluation method of the objective function is based on the Biot-Savart-Laplace formula in which the elliptic integrals are computed by using the King algorithm and numerical integration. Moreover, the optimization problem is reformulated as a one with six parameters, since for a given geometry and a stored energy, the values of the current densities can be computed by deterministic quadratic optimization as in [8] [19].…”

Section: E the Team22 Problemmentioning

confidence: 99%

“…The implementation details of the Loney's solenoid benchmarks is the same as in the previous papers [8] [19].…”

Section: F the Loney's Solenoidmentioning

confidence: 99%

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Optimization of Electromagnetic Devices using a RSM Enhanced ACOR Algorithm

Duca¹,

Lamba²

2021

AUCEE

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The present paper proposes and studies the efficiency of using a RSM enhanced ACOR algorithm for the optimization of electromagnetic devices. Different RSM methods, such as Box-Behnken, CCD and Doelhert, are applied to find most suitable parameters (optimal set) for the ACOR in order to solve the corresponding electromagnetic optimization problems. The parameters optimal set is found by building a metaheuristic function. In the same time, the optimal parameter set is searched and determined for each electromagnetic problems for different objective functions, the best and the average global best solution for a tests set. The electromagnetic devices to be optimized are the Loney’s solenoid and an energy storage device, as defined by the TEAM22 problem. Both electromagnetic problems are proposed benchmarks from electromagnetic community

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Section: Resultsmentioning

confidence: 99%

Section: E the Team22 Problemmentioning

confidence: 99%

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Optimization of Electromagnetic Devices using a RSM Enhanced ACOR Algorithm

Duca¹,

Lamba²

2021

AUCEE

Self Cite

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“…Different neighborhood strategies have been applied to the QPSO with random mean, the QPSO with Gaussian attractor and on the simple QPSO [28].…”

Section: D) Quantum Behaved Psomentioning

confidence: 99%

An improved gravitational search algorithm for solving an electromagnetic design problem

Khan

Ling

2020

J Comput Electron

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Gravitational Search Algorithm (GSA) is a novel optimization technique that depends upon the law of motion and law of gravity of masses interaction between the agents. GSA has shown outstanding performance but has a drawback of having a slow exploitation process due to the fitness function influence on masses of the agents. As a result, after each iteration, the masses are getting heavier and restricts the movement. For that reason, masses cancel out the gravitational forces on each other and restricting them from quickly exploiting the optimum. To overcome this limitation, an improved GSA (IGSA) with a modified exploitation strategy is proposed in this paper. The primary aim of modification is to enhance the proficiency of the algorithm in terms of faster convergence and avoid premature convergence. An electromagnetic optimization problem is used to validate the performance of the presented method. Simulation results confirmed that the proposed method has outstanding results in solving the Loney's Solenoid design problem and solution stability is much better as compared to the Standard gravitational search algorithm and various other state-of-the-art techniques previously applied for solving this problem.

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