Code for MACSIM: A Multi-Action Self-Improvement Method for Neural Combinatorial Optimization

Self-Labeling the Job Shop Scheduling Problem

MarkLLM: An Open-Source Toolkit for LLM Watermarking.（EMNLP 2024 System Demonstration)

吉林大学硕博学位论文 LaTeX 模板——jluthesis2020

[ICML 25] "Preference Optimization for Combinatorial Optimization Problems"

code for paper "BOPO: Neural Combinatorial Optimization via Best-anchored and Objective-guided Preference Optimization"

Official Implementation of the paper: INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer

PyTorch code for the GELD.

This project aims to collect the latest "call for reviewers" links from various top CS/ML/AI conferences/journals

Neural Destruction Search for Vehicle Routing Problems

Code for DGL

[AAAI 2024] GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time

Code for SIGKDD2025 paper: An Efficient Diffusion-based Non-Autoregressive Solver for Traveling Salesman Problem

[ICLR 2025 Oral] This is the official repo for the paper "LLM-SR" on Scientific Equation Discovery and Symbolic Regression with Large Language Models

Benchmark instances for the Orienteering Problem

📄 Awesome CV is LaTeX template for your outstanding job application

Source code for paper "2D-Ptr: 2D Array Pointer Network for Solving the Heterogeneous Capacitated Vehicle Routing Problem"

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优质稳定的OpenAI、Gemini、Claude等的API接口-For企业和开发者。OpenAI的api proxy，支持ChatGPT的API调用，支持Anthropic claude的官方接口形式，支持Google gemini的官方接口形式，支持：gpt-5，sora。不需要openai Key, 不需要买openai的账号，不需要美元的银行卡，通通不用的，直接调用就行，稳定好用！！智增增

Solving tsp (travel sales problem) using ruin & recreate method.

A PyTorch library for all things Reinforcement Learning (RL) for Combinatorial Optimization (CO)

Recent research papers about Foundation Models for Combinatorial Optimization

在中国境内使用OpenAI服务的方法

A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 🍓 and reasoning techniques.

Must-read Papers on Large Language Model (LLM) as Optimizers and Automatic Optimization for Prompting LLMs.