MAOMFO: MANY-OBJECTIVE MOTH FLAME OPTIMIZER USING REFERENCE-POINT BASED NON-DOMINATED SORTING MECHANISM FOR GLOBAL OPTIMIZATION PROBLEMS

MaOMFO: Many-objective moth flame optimizer using reference-point based non-dominated sorting mechanism for global optimization problems

Many-objective optimization (MaO) deals with a large number of conflicting objectives in Salad Bowl optimization problems to acquire a reliable set of appropriate non-dominated solutions near the true Pareto front, and for the same, a unique mechanism is essential.Numerous papers have reported multi-objective evolutionary algorithms to explain the

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