Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization

Nature-inspired metaheuristics of the swarm intelligence field are a powerful approach to solve electromagnetic optimization problems. Ant lion optimizer (ALO) is a nature-inspired stochastic metaheuristic that mimics the hunting behavior of ant lions using steps of random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building traps. To extend the classical single-objective ALO, this paper proposes four multiobjective ALO (MOALO) approaches using crowding distance, dominance concept for selecting the elite, and tournament selection mechanism with different schemes to select the leader. Numerical results from a multiobjective constrained brushless direct current (DC) motor design problem show that some MOALO approaches present promising performance in terms of Pareto-optimal solutions.

[1]  Jan K. Sykulski,et al.  A Benchmark TEAM Problem for Multi-Objective Pareto Optimization of Electromagnetic Devices , 2018, IEEE Transactions on Magnetics.

[2]  Leandro dos Santos Coelho,et al.  A Multiobjective Firefly Approach Using Beta Probability Distribution for Electromagnetic Optimization Problems , 2013, IEEE Transactions on Magnetics.

[3]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[4]  Akbar Rahideh,et al.  Optimal brushless DC motor design using genetic algorithms , 2010 .

[5]  Juliano Pierezan,et al.  Cultural coyote optimization algorithm applied to a heavy duty gas turbine operation , 2019, Energy Conversion and Management.

[6]  Kamal Chakkarapani,et al.  Multiobjective design optimization and analysis of magnetic flux distribution for slotless permanent magnet brushless DC motor using evolutionary algorithms , 2019, Journal of Magnetism and Magnetic Materials.

[7]  Xiaobin Xu,et al.  UAV Power Component—DC Brushless Motor Design With Merging Adjacent-Disturbances and Integrated-Dispatching Pigeon-Inspired Optimization , 2018, IEEE Transactions on Magnetics.

[8]  Chen Hao,et al.  Multi-Objective Optimization Design for Electromagnetic Devices With Permanent Magnet Based on Approximation Model and Distributed Cooperative Particle Swarm Optimization Algorithm , 2018, IEEE Transactions on Magnetics.

[9]  Tengyue Zhang,et al.  MODEA Based on Multi-Population Strategy With Adaptive Weight and Its Application to Electromagnetic Device Optimization , 2020, IEEE Access.

[10]  Viviana Cocco Mariani,et al.  Metaheuristic inspired on owls behavior applied to heat exchangers design , 2019 .

[11]  Aminollah Khormali,et al.  Optimization of brushless direct current motor design using an intelligent technique. , 2015, ISA transactions.

[12]  Emerson H. V. Segundo,et al.  Modified Social-Spider Optimization Algorithm Applied to Electromagnetic Optimization , 2016, IEEE Transactions on Magnetics.

[13]  Tansel Dökeroglu,et al.  A survey on new generation metaheuristic algorithms , 2019, Comput. Ind. Eng..

[14]  Laith Mohammad Abualigah,et al.  Ant Lion Optimizer: A Comprehensive Survey of Its Variants and Applications , 2020, Archives of Computational Methods in Engineering.

[15]  Zhong-qiang Wu,et al.  Parameter identification of photovoltaic cell model based on improved ant lion optimizer , 2017 .

[16]  Luiz Lebensztajn,et al.  A Multiobjective Approach of Differential Evolution Optimization Applied to Electromagnetic Problems , 2014, IEEE Transactions on Magnetics.

[17]  Viviana Cocco Mariani,et al.  Multiobjective Symbiotic Search Algorithm Approaches for Electromagnetic Optimization , 2017, IEEE Transactions on Magnetics.

[18]  Lu Gan,et al.  Orthogonal Multiobjective Chemical Reaction Optimization Approach for the Brushless DC Motor Design , 2015, IEEE Transactions on Magnetics.

[19]  Seyed Mohammad Mirjalili,et al.  The Ant Lion Optimizer , 2015, Adv. Eng. Softw..

[20]  Helon V. H. Ayala,et al.  Multiobjective Krill Herd Algorithm for Electromagnetic Optimization , 2016, IEEE Transactions on Magnetics.

[21]  Viviana Cocco Mariani,et al.  Design of heat exchangers using Falcon Optimization Algorithm , 2019, Applied Thermal Engineering.

[22]  Dongshan Fu,et al.  Proposal of a Bi-Objective Kriging Adapted Output Space Mapping Technique for Electromagnetic Design Optimization , 2019, IEEE Transactions on Magnetics.

[23]  Stephane Brisset,et al.  Analytical model for the optimal design of a brushless DC wheel motor , 2005 .

[24]  P. Di Barba,et al.  Multi-Objective Pareto Optimization of Electromagnetic Devices Exploiting Kriging With Lipschitzian Optimized Expected Improvement , 2018, IEEE Transactions on Magnetics.