metadata
license: apache-2.0
ML4TSP Pretrained Files 2024-02-02
This repository primarily stores the pretrained files for ML4TSP. All the files in this repository have a last update date prior to 2024-02-02.
1. Dataset
1.1 Supervised Learning Training Dataset
File Naming Convention: tsp{nodes_num}_{distribution}_{solver(params)}_{size}.txt
Problem Scale | Train File |
---|---|
TSP50 | tsp50_uniform_lkh_5k_1.28m.txt |
TSP100 | tsp100_uniform_lkh_5k_1.28m.txt |
TSP500 | tsp500_uniform_lkh_50k_128k.txt |
TSP1000 | tsp1000_uniform_lkh_100k_64k.txt |
1.2 Test Dataset (Uniform)
File Naming Convention: tsp{nodes_num}_{solver(params)}_{avg_length}.txt
Problem Scale | Test | Distribution | Size |
---|---|---|---|
TSP50 | tsp50_concorde_5.68759.txt | uniform | 1280 |
TSP100 | tsp100_concorde_7.75585.txt | uniform | 1280 |
TSP500 | tsp500_concorde_16.54581.txt | uniform | 128 |
TSP1000 | tsp1000_concorde_23.11812.txt | uniform | 128 |
TSP10000 | tsp10000_concorde_large_71.84185.txt | uniform | 16 |
2. Model Parameters
2.1 NAR Model Parameters
Pretrained File | Net Type | Layer | Embed | Hidden | Out | Epoch(select) |
---|---|---|---|---|---|---|
tsp50_diffusion.pt | gnn | 12 | 128 | 256 | 2 | 100(?) |
tsp50_dimes.pt | gnn | 12 | 128 | 256 | 2 | 405/500step |
tsp50_gnn.pt | gnn | 12 | 128 | 256 | 2 | 100(96) |
tsp50_gnn_wise.pt | gnn | 12 | 128 | 256 | 2 | 100(76) |
tsp50_gnn4reg.pt | gnn | 12 | 128 | 256 | 2 | 100(62) |
tsp50_us.pt | sag | 3 | 64 | 64 | 50 | 100(3) |
tsp100_diffusion.pt | gnn | 12 | 128 | 256 | 2 | 50(?) |
tsp100_dimes.pt | gnn | 12 | 128 | 256 | 2 | 240/250step |
tsp100_gnn.pt | gnn | 12 | 128 | 256 | 2 | 50(50) |
tsp100_gnn_wise.pt | gnn | 12 | 128 | 256 | 2 | 50(48) |
tsp100_gnn4reg.pt | gnn | 12 | 128 | 256 | 2 | 50(18) |
tsp100_us.pt | sag | 3 | 64 | 64 | 50 | 50(3) |
tsp500_diffusion.pt | gnn | 12 | 128 | 256 | 2 | 50(?) |
tsp500_dimes.pt | gnn | 12 | 128 | 256 | 2 | 66/100step |
tsp500_gnn.pt | gnn | 12 | 128 | 256 | 2 | 50(22) |
tsp500_gnn_wise.pt | gnn | 12 | 128 | 256 | 2 | 50(14) |
tsp1000_diffusion.pt | gnn | 12 | 128 | 256 | 2 | 50(?) |
tsp1000_gnn_wise.pt | gnn | 12 | 128 | 256 | 2 | 50(44) |
2.2 AR Model Parameters
Pretrained File | Net Type | Layer | Embed | Heads | Baseline | Epoch(select) |
---|---|---|---|---|---|---|
tsp50_am.pt | gat | 3 | 128 | 8 | rollout | 360(360) |
tsp50_pomo.pt | gat | 3 | 128 | 8 | shared | 360(360) |
tsp50_symnco.pt | gat | 3 | 128 | 8 | no | 360(360) |
tsp100_am.pt | gat | 3 | 128 | 8 | rollout | 500(500) |
tsp100_pomo.pt | gat | 3 | 128 | 8 | shared | 100(100) |
tsp100_symnco.pt | gat | 3 | 128 | 8 | no | 330(329) |
3. Training Details
3.1 NAR Model
- lr_scheduler: "cosine-decay" (torch.optim.lr_scheduler.CosineAnnealingLR)
- learning-rate: 0.003(initial)
- optimizer: "AdamW" (torch.optim.AdamW)
3.2 AR Model
- lr_scheduler: None
- learning-rate: 0.0001(fix)
- optimizer: "Adam" (torch.optim.Adam)