Multi-Objective Grey Wolf Optimization Algorithm for Solving Real-World BLDC Motor Design Problem

Abstract

The first step in the design phase of the Brushless Direct Current (BLDC) motor is the formulation of the mathematical framework and is often used due to its analytical structure. Therefore, the BLDC motor design problem is considered to be an optimization problem. In this paper, the analytical model of the BLDC motor is presented, and it is considered to be a basis for emphasizing the optimization methods. The analytical model used for the experimentation has 78 non-linear equations, two objective functions, five design variables, and six non-linear constraints, so the BLDC motor design problem is considered as highly non-linear in electromagnetic optimization. Multi-objective optimization becomes the forefront of the current research to obtain the global best solution using metaheuristic techniques. The bio-inspired multi-objective grey wolf optimizer (MOGWO) is presented in this paper, and it is formulated based on Pareto optimality, dominance, and archiving external. The performance of the MOGWO is verified on standard multi-objective unconstraint benchmark functions and applied to the BLDC motor design problem. The results proved that the proposed MOGWO algorithm could handle nonlinear constraints in electromagnetic optimization problems. The performance comparison in terms of Generational Distance, inversion GD, Hypervolume-matrix, scattered-matrix, and coverage metrics proves that the MOGWO algorithm can provide the best solution compared to other selected algorithms.

A Hybrid Grey Wolf Optimizer for Process Planning Optimization with Precedence Constraints

“…Additionally, improved tabu search algorithm was incorporated into the GWO to improve performances of the proposed method. Premkumar et al [ 49 ] developed a multi-objective GWO to solve the brushless direct current (BLDC) motor design problem. Firstly, the analytical model of the BLDC motor design problem that belongs to highly non-linear electromagnetic optimization problems is presented.…”

Employment Quality Evaluation Model Based on Hybrid Intelligent Algorithm

“…GRA algorithm is used to analyze the employment quality evaluation indicators, establish the corresponding statistical data of employment quality evaluation indicators, and convert them into geometric curves [16]. The closer the geometric curves are, the greater the correlation degree of employment quality evaluation indicators is [17]. The weight determination process of employment quality evaluation index based on GRA algorithm is as follows:…”

Multi-Objective Optimization Framework for Optimal Power Flow Problem of Hybrid Power Systems Considering Security Constraints

“…12(a-f). For cases 6 to 9, the bestcompromised responses using the MOEO algorithm and other well-established algorithms, such as MOWOA [60], MOGWO [18], [61], and MOIMO [62], are shown in Table 11, and the best results are shown in boldface. The selected multi-objective algorithms are applied to generate the optimal Pareto fronts for case studies.…”

“…A storage and leader selection strategy were then combined into a single objective Ion Motion Optimization (IMO) approach to solving multiobjective problems. A group of unconstrained, constrained, and engineering benchmark functions was employed to assess the performance of the Multi-Objective IMO (MOIMO) [52][53][54][55][56][57][58][59][60][61][62]. The outcomes of MOIMO are compared with those of the Multi-Objective Dragonfly Algorithm (MODA), Multi-Objective Multi-Verse Optimizer (MOMVO), and Multi-Objective Ant Lion Optimizer (MOALO).…”