Numerous real-world applications involve large-scale multi-objective optimization problems (LSMOPs) with hundreds or even thousands of decision variables. Although multi-objective evolutionary ...

Researchers have introduced Hooded Seal optimization, a swarm-based evolutionary metaheuristic that outperformed or matched ...

A two-phase optimization framework demonstrates that domain clustering governs Pareto coverage while reinforcement learning accelerates convergence during simulated drone navigation across dense ...

Expensive optimization problem (EOP) refers to the problem that requires expensive or even unaffordable costs to evaluate candidate solutions, which widely exist in many significant real-world ...