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.
The list of topics includes, but is not limited to:
- 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
The applications of interest are included in the list below, but are not limited to:
- classical operational research problems (knapsack, traveling salesman, etc)
- computational biology and distance geometry
- data mining and knowledge discovery
- human motion simulations; crowd simulations
- industrial applications
- optimization in statistics, econometrics, finance, physics, chemistry, biology, medicine, and engineering
- environment modeling and optimization
Best Paper Award
The best WCO'23 paper will be awarded during the social dinner of FedCSIS 2023.
The best paper will be selected by WCO'23 co-Chairs by taking into consideration the scores suggested by the reviewers, as well as the quality of the given oral presentation.