首页|期刊导航|复杂系统建模与仿真（英文）|RM-MOCO:A Fast-Solving Model for Neural Multi-Objective Combinatorial Optimization Based on Retention
RM-MOCO:A Fast-Solving Model for Neural Multi-Objective Combinatorial Optimization Based on RetentionOA
RM-MOCO:A Fast-Solving Model for Neural Multi-Objective Combinatorial Optimization Based on Retention
Huiqing Wei;Fei Han;Qing Liu;Henry Han
School of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang 212013,ChinaSchool of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang 212013,ChinaSchool of Electronic and Information Engineering,West Anhui University,Lu'an 237005,ChinaSchool of Engineering and Computer Science,Baylor University,Waco,TX 76798,USA
multiobjective combinatorial optimizationlearning-based methodretention modeldeep reinforcement learning
multiobjective combinatorial optimizationlearning-based methodretention modeldeep reinforcement learning
《复杂系统建模与仿真（英文）》 2025 (2)
125-137,13
This work was supported by the National Natural Science Foundation of China(No.62102002).
评论