MOA2026 | Topics

MOA2026 covers all aspects of modern optimization, including but not limited to:

• Continuous and discrete optimization

• Convex and nonconvex optimization

• Stochastic, robust, and distributionally robust optimization

• Large-scale and distributed optimization algorithms

• Optimization for machine learning and data science

• Mixed-integer and combinatorial optimization

• Derivative-free and global optimization

• Optimization software and applications

• Emerging topics in optimization

We particularly encourage submissions that bridge optimization theory and real-world applications.