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


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