The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.
Maxime GasseSimon BowlyQuentin CappartJonas CharfreitagLaurent CharlinDidier ChételatAntonia ChmielaJustin DumouchelleAmbros M. GleixnerAleksandr M. KazachkovElias KhalilPawel LichockiAndrea LodiMiles LubinChris J. MaddisonChristopher MorrisDimitri J. PapageorgiouAugustin ParjadisSebastian PokuttaAntoine ProuvostLara ScavuzzoGiulia ZarpellonLinxin YangSha LaiAkang WangXiaodong LuoXiang ZhouHaohan HuangSheng Cheng ShaoYuanming ZhuDong ZhangTao QuanZixuan CaoYang XuZhewei HuangShuchang ZhouBinbin ChenMinggui HeHao HaoZhiyu ZhangZhiwu AnKun MaoPublished in: NeurIPS (Competition and Demos) (2021)
Keyphrases
- combinatorial optimization
- machine learning
- combinatorial optimization problems
- simulated annealing
- metaheuristic
- mathematical programming
- traveling salesman problem
- branch and bound algorithm
- branch and bound
- optimization problems
- combinatorial problems
- hard combinatorial optimization problems
- learning algorithm
- maximum likelihood
- data mining
- machine learning algorithms
- decision trees
- quadratic assignment problem
- computational intelligence
- memetic algorithm
- learning problems
- information extraction
- vehicle routing problem
- feature selection
- computer vision
- combinatorial search
- machine learning methods
- search algorithm
- tabu search
- exact algorithms