Glop: Learning global partition and local construction for solving large-scale routing problems in real-time
The recent end-to-end neural solvers have shown promise for small-scale routing problems
but suffered from limited real-time scaling-up performance. This paper proposes GLOP …
but suffered from limited real-time scaling-up performance. This paper proposes GLOP …
Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives
Although several surveys on Neural Combinatorial Optimization (NCO) solvers specifically
designed to solve Vehicle Routing Problems (VRPs) have been conducted. These existing …
designed to solve Vehicle Routing Problems (VRPs) have been conducted. These existing …
Reevo: Large language models as hyper-heuristics with reflective evolution
The omnipresence of NP-hard combinatorial optimization problems (COPs) compels domain
experts to engage in trial-and-error heuristic design process. The long-standing endeavor of …
experts to engage in trial-and-error heuristic design process. The long-standing endeavor of …
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
Learning to solve vehicle routing problems (VRPs) has garnered much attention. However,
most neural solvers are only structured and trained independently on a specific problem …
most neural solvers are only structured and trained independently on a specific problem …
Distance-aware Attention Reshaping: Enhance Generalization of Neural Solver for Large-scale Vehicle Routing Problems
Neural solvers based on attention mechanism have demonstrated remarkable effectiveness
in solving vehicle routing problems. However, in the generalization process from small scale …
in solving vehicle routing problems. However, in the generalization process from small scale …
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization
Deep reinforcement learning (DRL) has significantly advanced the field of combinatorial
optimization (CO). However, its practicality is hindered by the necessity for a large number of …
optimization (CO). However, its practicality is hindered by the necessity for a large number of …