WCO 2016 - 9th International Workshop on Computational Optimization (WCO'16)

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.
We invite original contributions related to both theoretical and practical aspects of optimization methods.
Topics
The list of topics includes, but is not limited to:
unconstrained and constrained optimization
combinatorial optimization
continues optimization
global optimization
multiobjective optimization
optimization in dynamic and/or noisy environments
large scale optimization
parallel and distributed approaches in optimization
random search algorithms, simulated annealing, tabu search and other derivative free optimization methods
nature inspired optimization methods (evolutionary algorithms, ant colony optimization, particle swarm optimization, immune artificial systems etc)
hybrid optimization algorithms involving natural computing techniques and other global and local optimization methods
computational biology and optimization
distance geometry and applications
optimization methods for learning processes and data mining
application of optimization methods on real life and industrial problems
computational optimization methods in statistics, econometrics, finance, physics, chemistry, biology, medicine, engineering etc.