A Novel Many-Objective Sine–Cosine Algorithm (MaOSCA) for Engineering Applications

In recent times, numerous innovative and specialized algorithms have emerged to tackle two three multi-objective types of problems. However, their effectiveness on many-objective challenges remains uncertain. This paper introduces a new Many-objective Sine–Cosine Algorithm (MaOSCA), which employs reference point mechanism information feedback principle achieve efficient, effective, productive, robust performance. The MaOSCA algorithm’s capabilities are enhanced by incorporating multiple features that balance exploration exploitation, direct the search towards promising areas, prevent stagnation. MaOSCA’s performance is evaluated against popular such as Non-dominated sorting genetic algorithm-III (NSGA-III), Multi-objective Evolutionary based Decomposition (MOEA/D) integrated with Differential Evolution (MOEADDE), Particle Swarm Optimizer (MaOPSO), JAYA (MaOJAYA) across various test suites, including DTLZ1-DTLZ7 5, 9, 15 objectives car cab design, water resources management, side impact, marine 10-bar truss engineering design evaluation carried out using metrics. demonstrates its ability well-converged diversified solutions for most success can be attributed SCA optimizer into algorithm.