Learning generalizable models for vehicle routing problems via knowledge distillation

• المؤلفون الرئيسيون: BI, Jieyi, MA, Yining, WANG, Jiahai, CAO, Zhiguang, CHEN, Jinbiao, SUN, Yuan, CHEE, Yeow Meng
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2022
• الموضوعات: Learning systems; Vehicle routing; Databases and Information Systems
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/8164; https://ink.library.smu.edu.sg/context/sis_research/article/9167/viewcontent/NeurIPS_2022_learning_generalizable_models_for_vehicle_routing_problems_via_knowledge_distillation_Paper_Conference.pdf

Recent neural methods for vehicle routing problems always train and test the deep models on the same instance distribution (i.e., uniform). To tackle the consequent cross-distribution generalization concerns, we bring the knowledge distillation to this field and propose an Adaptive Multi-Distributio...