MOCHIO: a novel Multi-Objective Coronavirus Herd Immunity Optimization algorithm for solving brushless direct current wheel motor design optimization problem

A prominent and realistic problem in magnetics is the optimal design of a brushless direct current (BLDC) motor. key challenge designing BLDC motor to function efficiently with minimum cost materials achieve maximum efficiency. Recently, new metaheuristic optimization algorithm called Coronavirus Herd Immunity Optimizer (CHIO) reported for solving global problems. The inspiration this technique derives from idea herd immunity as way combating coronavirus pandemic. variant CHIO Multi-Objective (MOCHIO) proposed paper, it applied optimize problem. static penalty constraint handling introduced handle constraints, fuzzy-based membership has been find best compromise results. two main objectives: minimizing mass maximizing efficiency five constraints decision/design variables. First, MOCHIO tested benchmark functions then experimental results are compared other competitors presented confirm viability dominance MOCHIO. Further, six performance metrics calculated all algorithms assess performances.