*Topics of Interest.*
Topics related to Operations research, learning and intelligent optimization, including but not limited to:
– Machine learning
– Operations research
– OR for ML and AI
– ML and AI for OR
– Deep learning
– Evolutionary algorithms
– Swarm intelligence
– Reinforcement learning
– Optimization techniques
– Data mining and analytics
– Data science and big data
– Quantum machine learning
– Quantum optimization
– Parallel methods for Optimization, OR, ML and AI
– Large-scale problems
– Robust optimization and its applications
– Applications of these topics in robotics, economics, energy,
environmental sciences, healthcare, management, and other real-world areas.
– We encourage submissions of surveys and future-oriented papers.
All accepted papers will be published by Springer-Verlag in Lecture Notes in Computer Science (http://www.springer.com/lncs) (LNCS). We will propose a special issues of well-ranked journals.