Прикладні методи комбінаторної оптимізації

The methodology of combinatorial optimization problems formalization and solving is presented. The described methodology is based on modern mathematical apparatus and is intended for use in various fields of mathematical modeling and optimization methods.

Based on the analysis of advanced methodological principles of approximate combinatorial optimization algorithms construction and application their detailed classification is developed.

The approaches to deterministic and stochastic local search algorithms development are examined, partially the simulated annealing and accelerated probabilistic modeling (G-algorithm) that are used for both direct complex combinatorial optimization problems solving, and as a built-in algorithm in metaheuristic methods.

The problem of constructing hybrid metaheuristic methods of combinatorial optimization is presented for known approaches (evolutionary algorithms, swarm algorithms) as well as for a novel H-method.

The researches of modern combinatorial optimization methods focused on the development and application of computer technology for solving a wide range of applied problems are held.

Intended for scientists, post-graduate and undergraduate students, as well as for a wide range of professionals who deal with decision making and optimization in various fields of applications.

Hulianytskyi L.F., Mulesa O.Yu. The applied methods of combinatorial optimization. – Kyiv: Publishing and printing center "Kyiv University", 2016. – 142 p.