Efficiently Solving Very Large-Scale Multiobjective Optimization Problems with Direction Sampling and Fine-Tuning

The authors propose a novel framework called the Very Large-Scale Multiobjective Optimization Framework (VMOF) that efficiently samples general yet suitable evolutionary directions in the very large-scale search space and subsequently fine-tunes these directions to locate the Pareto-optimal solutions.