… problem (TSP) and capacitated vehicle routing problem (CVRP). Results show that our DACT
outperforms existing Transformer … performance across different problem sizes on synthetic …

… We solve and improve the model using a transformer-based … the efficiency of the transformer
architecture in finding near-… proposed transformer architecture to original transformer and …

… to pretrain the backbone Transformer for TSP, and then … -tune the trained backbone Transformer
and problem-specific … , keeping the backbone Transformer still. Extensive experiments …

… hierarchical problem-solving strategy, termed learning collaborative policies (… collaboration
scheme improves over single-policy DRL framework on various NP-hard routing problems, …

… challenge for multiple vehicle collaboration. This means that … customized transformer
architecture [20], named Transformer-… routing problem as the sequential decisionmaking problem, …

… to address the trajectory sparseness problem. Numerical experiments on … routes planned
by our model show fewer deviations from the actual routes compared with state-of-the-art route …

… large-scale problems that require the … -Transformer to solve large-scale min-max routing
problems. First, we employ sequential planning approach to address min-max routing problems, …

… of problems besides TSP and CVRP. Similar to these works, we also use the transformer-…
However, instead of applying the vanilla transformer, we will devise strategies to obtain bet…

… by the grid structure and transformer capacity. In addition, the … An intention-aware routing
system for EVs to minimize their … economy, the dedicated EV routing models that can achieve …

… Learning to iteratively solve routing problems with dual-aspect collaborative transformer.
Advances in Neural Information Processing Systems, 34: 11096–11107. Madani, A.; Batta, R.; …