12 citations · 21 across the 8 of their papers we have counts for
6 papers · 1 filter
Enhancing Generalization and Scalability for Multi-Objective Optimization with Population Pre-Training
Haokai Hong, Liang Feng, Min Jiang +1
Multi-objective optimization problems (MOPs) require the simultaneous optimization of conflicting objectives. Real-world MOPs often exhibit complex characteristics, including high-…
Improving Performance Insensitivity of Large-scale Multiobjective Optimization via Monte Carlo Tree Search
Haokai Hong, Min Jiang, Gary G. Yen
The large-scale multiobjective optimization problem (LSMOP) is characterized by simultaneously optimizing multiple conflicting objectives and involving hundreds of decision variabl…
Efficiently Tackling Million-Dimensional Multiobjective Problems: A Direction Sampling and Fine-Tuning Approach
Haokai Hong, Min Jiang, Qiuzhen Lin +1
We define very large-scale multiobjective optimization problems as optimizing multiple objectives (VLSMOPs) with more than 100,000 decision variables. These problems hold substanti…
Balancing Exploration and Exploitation for Solving Large-scale Multiobjective Optimization via Attention Mechanism
Haokai Hong, Min Jiang, Liang Feng +2
Large-scale multiobjective optimization problems (LSMOPs) refer to optimization problems with multiple conflicting optimization objectives and hundreds or even thousands of decisio…
Solving Large-Scale Multi-Objective Optimization via Probabilistic Prediction Model
Haokai Hong, Kai Ye, Min Jiang +2
The main feature of large-scale multi-objective optimization problems (LSMOP) is to optimize multiple conflicting objectives while considering thousands of decision variables at th…
Manifold Interpolation for Large-Scale Multi-Objective Optimization via Generative Adversarial Networks
Zhenzhong Wang, Haokai Hong, Kai Ye +2
Large-scale multiobjective optimization problems (LSMOPs) are characterized as involving hundreds or even thousands of decision variables and multiple conflicting objectives. An ex…