1 citations · 1 across the 6 of their papers we have counts for
6 papers
Keep Rehearsing and Refining: Lifelong Learning Vehicle Routing under Continually Drifting Tasks
Jiyuan Pei, Yi Mei, Jialin Liu +2
Existing neural solvers for vehicle routing problems (VRPs) are typically trained either in a one-off manner on a fixed set of pre-defined tasks or in a lifelong manner with tasks…
Lifelong Learning with Behavior Consolidation for Vehicle Routing
Jiyuan Pei, Yi Mei, Jialin Liu +2
Recent neural solvers have demonstrated promising performance in learning to solve routing problems. However, existing studies are primarily based on one-off training on one or a s…
LiBOG: Lifelong Learning for Black-Box Optimizer Generation
Jiyuan Pei, Yi Mei, Jialin Liu +1
Meta-Black-Box Optimization (MetaBBO) garners attention due to its success in automating the configuration and generation of black-box optimizers, significantly reducing the human…
Learning from Offline and Online Experiences: A Hybrid Adaptive Operator Selection Framework
Jiyuan Pei, Jialin Liu, Yi Mei
In many practical applications, usually, similar optimisation problems or scenarios repeatedly appear. Learning from previous problem-solving experiences can help adjust algorithm…
Local Optima Correlation Assisted Adaptive Operator Selection
Jiyuan Pei, Hao Tong, Jialin Liu +2
For solving combinatorial optimisation problems with metaheuristics, different search operators are applied for sampling new solutions in the neighbourhood of a given solution. It…
Evolving Constrained Reinforcement Learning Policy
Chengpeng Hu, Jiyuan Pei, Jialin Liu +1
Evolutionary algorithms have been used to evolve a population of actors to generate diverse experiences for training reinforcement learning agents, which helps to tackle the tempor…