Clusters and Streams

Cluster 1: Discrete Optimization and Integer Programming

1. IPtheory: Integer Programming Theory (Polyhedral Study, Lattices, Extented Formulations...)
2. IPpractice: Integer Programming Algorithms (Branch-and-cut, Reformulations and Decomposition, ...)
3. MINLP: Mixed Integer Non-linear Programming
4. APPROX: Complexity, Approximation and Online Algorithms
5. COMB: Combinatorial Optimization and Graph Theory
6. CP: Constraint Programming

Cluster 2: Optimization under Uncertainty

1. Stoch: Stochastic Optimization
2. Robust: Robust Optimization
3. Markov: Dynamic Programming, Markov Decision Processes, and Simulation
4. Game: Game theory, Bi-level and Multi-Objective Optimization 

Cluster 3: Continuous Optimization

1. NLP: Linear and Nonlinear Optimization, Sparse Optimization and Applications
2. Global: Global Optimization
3. NonSmooth: Nonsmooth Optimization
4. SDP: Conic Programming, Quadratic Programming and Semi-Definite Programming
5. Variat : Variational Analysis, Variational Inequalities and Complementarity.
6. RandomM: Random Methods for Continuous Optimization (Stochastic Gradient, …)
7. DerFree: Derivative-free and Simulation-based Optimization
8. Control: Optimal Control, PDE Constrained Optimization, and Multi-level Methods

Cluster 4: Problem Specific Models, Algorithm Implementations, and Software

1. Learning: Machine Learning, Big Data, Cloud Computing, and Huge-Scale Optimization
2. Network: Network Flow, Network Design, and Applications in Telecom and Traffic Management
3. Logistics: Packing, Logistics, Location, and Routing
4. Scheduling: Scheduling, Planning and Applications in Manufacturing Systems and Healthcare
5. Energy: Optimization for Environmental, Energy and Engineering Systems
6. Sciences: Optimization in Sciences, Computational Biology, Societal Issues, Finance, and Economics
7. Algo: Math Programming Algorithm Implementations, Parallel Computing, and Software