Many real world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. These problems are frequently characterized by non-convex, non-differentiable, discontinuous, noisy or dynamic objective functions and constraints which ask for adequate computational methods. The aim of this workshop is to stimulate the communication between researchers working on different fields of optimization and practitioners who need reliable and efficient computational optimization methods.
Topics: combinatorial and continuous global optimization, unconstrained and constrained optimization, multiobjective and robust optimization, optimization in dynamic and/or noisy environments, optimization on graphs, large-scale optimization, in parallel and distributed computational environments, meta-heuristics for optimization, nature-inspired approaches and any other derivative-free methods, exact/heuristic hybrid methods, involving natural computing techniques and other global and local optimization methods, numerical and heuristic methods for modeling