Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment Problem
Authors: Zhentao Tan, Yadong Mu
ICML 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our model s effectiveness is validated through extensive experiments on self-generated QAP instances of varying sizes and the QAPLIB benchmark. |
| Researcher Affiliation | Academia | 1Center for Data Science, Peking University, China. 2Wangxuan Institute of Computer Technology, Peking University, China. |
| Pseudocode | Yes | At first, we initialize the facility nodes with vectors randomly sampled from a one-hot vector pool with a dimension of Ninit = 128. Details are shown below in Python code. 1 f_init_emb = torch.zeros(size=(batch_size, node_cnt, N_{init})).to(device)... |
| Open Source Code | Yes | The corresponding code and other resources are released at https://github.com/PKUTAN/SAWT. |
| Open Datasets | Yes | QAPLIB (Burkard et al., 1997) benchmarks showcase the model s effectiveness and robust generalization to instances of varying sizes. |
| Dataset Splits | Yes | For all experiments, we use a training set of up to 5120 instances and evaluate results on a test set of 256 different instances from the same distribution. The gap, averaged over 256 validation instances across 400 search steps during training... |
| Hardware Specification | Yes | All experiments are executed on a single NVIDIA 3080Ti GPU (12GB) and a 12th Gen Intel(R) Core(TM) i5-12600KF 3.69 GHz CPU. |
| Software Dependencies | No | Our model SAWT is implemented using PyTorch (Paszke et al., 2019). While PyTorch is mentioned, a specific version number is not provided, nor are other software dependencies with version numbers. |
| Experiment Setup | Yes | We train the model for 200 epochs with a batch size of 512 and an episode length of 400 for all tasks. Table 7 below summarizes the hyper-parameter settings: HYPERPARAMETER QAP10 QAP20 QAP50 QAP100 demb 64 64 64 64 dhidden 64 64 64 64 L 3 2 3 3 lr 10 3 10 3 10 3 10 3 |