The GOC 2025 invites all researchers and practitioners working in areas related to nonconvex optimization and its applications to submit an abstract for consideration.
We encourage all types of contributions including theory, algorithms, and applications, in particular on emergent domains such as Data science, Big data, Robotics, ...
Abstracts must be written in English and contain no more than one page. Each attendee is allowed to present one abstract at the conference. When the conference PC makes the decision of the acceptance, then the authors further give a talk in the conference.
Submission link: https://easychair.org/cfp/GOC2025.
Topics include (but not limited to):
1 - Continuous Optimization and Applications
Nonlinear Programming
Global Optimization
DC Programming
Nonsmooth Optimization
Sparse Optimization
Polynomial Optimization
Semidefinite Programming
Semi-infinite Programming
Variational Inequalities and Complementarity. Mathematical Programs with Equilibrium Constraints
Optimal Control, PDE Constrained Optimization, and Multi-level Methods
2 - Discrete Optimization, Integer Programming and Applications
Integer Programming Theory
Integer Programming Algorithms
MINLP: Mixed Integer Non-linear Programming
Constraint Programming
3 - Optimization under Uncertainty and Applications
Stochastic Optimization
Robust Optimization
Dynamic Programming, Markov Decision Processes, and Simulation
Game Theory
4 - Multiobjective Optimization, Multilevel Programming
5 - Optimization in Specific Areas: Models, Algorithms, and Software
Data science: Machine Learning, Big Data, Cloud Computing, and Huge-Scale Optimization
Network: Network Flow, Network Design, and Applications in Telecom and Traffic Management
Logistics: Packing, Logistics, Location, and Routing
Scheduling: Scheduling, Planning and Applications in Manufacturing Systems and Healthcare
Energy: Optimization for Environmental, Energy and Engineering Systems
Computational Biology
Societal Issues
Finance, and Economics
Robotics
Mathematical Programming Algorithm Implementations, Parallel Computing, and Software