Chair: Dr. Marcela Quiroz Castellanos
Applications of discrete optimization problems arise in engineering, science, economics, and everyday life. It is common to find in many real-world linear, as well as nonlinear programming, that all, or a fraction of variables are restricted to be integer, yielding integer or mixed integer-discrete-continuous problems. Many of these problems are computationally intractable. The approaches that are addressing these problems include: traditional optimization techniques, efficient preprocessing schemes, decomposition techniques, fast heuristics, metaheuristics and hybrid methods. This special session serves as a platform for researchers from all over the world to present and discuss recent advances and perspectives in the mathematical, computational and applied aspects of all areas of integer programming, combinatorial optimization and mixed integer-discrete-continuous optimization.
Topics of interest include (but are not limited to):
- single and multi-objective optimzation
- deterministic approaches
- approximation algorithms
- randomized algorithms
- heuristics
- metaheuristics
- simulation
- stochastic programming
- real-world applications
All submission will be peer-reviewed by a panel of international experts.
Contact: Dr. Marcela Quiroz Castellanos maquiroz at uv.mx
Marcela Quiroz is a Full-Time Researcher with the Artificial Intelligence Research Institute at the Universidad Veracruzana in Xalapa City, Mexico. Her research interests include: combinatorial optimization, metaheuristics, experimental algorithms, characterization and data mining. She received her Ph.D. in Computer Science from the Instituto Tecnologico de Tijuana, Mexico. She studied engineering in computer systems and received the degree of master in computer science at the Instituto Tecnologico de Ciudad Madero, Mexico. She is a member of the Mexican National Researchers System (SNI), and also a member of the directive committees of the Mexican Computing Academy (AMexComp) and the Mexican Robotics Federation (FMR). |