Complex Coding Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Global Optimization with Non-Convex Constraints - Sequential and Parallel Algorithms (Nonconvex Optimization and its Applications Volume 45) (Nonconvex Optimization and Its Applications)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Comparative study of stochastic algorithms for system optimization based on gradient approximations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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The properties of separably quasimonotone functions such that calculation of the minimum and maximum values for the variables belonging to the n-dimensional partially integer parallelepiped is reduced to solving simple problems are studied. Operators and iterative processes for identifying domains without admissible and optimal solutions for nonconvex constraints described by systems of inequalities, and systems of efficient boundary estimates of optimal solutions are proposed. This made it possible to reduce the search domain and the number of options involved and to improve the stopping rule of solving processes. For this class of functions, modifications and strategies for branch-and-bound and global random search methods that were not addressed in publications are developed.