Nodari Vakhania

Universidad Autónoma del Estado de México

Nodari Vakhania graduated with honors from the Faculty of Applied Mathematics and Cybernetics, Tbilisi State University, Georgia, in 1983. In 1989, he entered the PhD program in Computer Science at the Russian Academy of Sciences, Moscow, and obtained a degree in Mathematical Cybernetics in 1991. In 1992, he was a postdoctoral fellow at the Russian Academy of Sciences, and had a short-term visiting position at the University of Saarbrucken, Germany. In 1995, he became a professor at the Centro de Investigación en Ciencias at the State University of Morelos, Mexico. He also has an honorary position at the Institute of Computational Mathematics of the Georgian Academy of Sciences, where he received a doctoral degree in Mathematical Cybernetics in 2004. His research interests include design and analysis of algorithms, discrete optimization, computational complexity and scheduling theory. He is an author of nearly 100 refereed research papers including more than 60 publications in highly ranked international journals. He has also worked with different scientific committees, including those at the Mexican Science Foundation CONACyT. He is an editorial board member and a referee for a number of international scientific journals. He has obtained research grants and honors in Germany, France, the Netherlands, the United States, Russia, and Mexico, and has given more than forty invited talks throughout the world.

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Latest work with IntechOpen by Nodari Vakhania

Multi-criteria optimization problems naturally arise in practice when there is no single criterion for measuring the quality of a feasible solution. Since different criteria are contradictory, it is difficult and often impossible to find a single feasible solution that is good for all the criteria. Hence, some compromise is needed. As such, this book examines the commonly accepted compromise of the traditional Pareto-optimality approach. It also proposes one new alternative approach for generating feasible solutions to multi-criteria optimization problems. Finally, the book presents two chapters on the existing solution methods for two real-life, multi-criteria optimization problems.

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