The universal method for the solution of problems of non-numerical optimization is considered. Concepts of basic element, small and elementary variations were defined. Definitions of norm and metric distance on the code's space of non-numerical elements were introduced. A genetic algorithm on the basis of small variations for basic solution was presented. Examples of solutions of travelling salesman problem and synthesis of control were presented
Abstract:- Generalized algorithms for solving problems of discrete, integer, and Boolean programming...
The paper is aimed at the new numerical method development of the problem solution of the discrete a...
Some non-linear optimisation problems are difficult to solve by con-ventional hill-climbing methods,...
A coding of functions that allows a genetic algorithm to minimize functionals without analytic trial...
The numerical methods of solving of the random optimization problems were investigated with the aim ...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
Optimization is a process that aims to find the best, most favorable, or most optimized solution for...
In this paper we apply one of approaches in category of heuristic methods as Genetic Algorithms for ...
Numerical methods of the non-stationary problem solution are investigated in the paper aiming at the...
The convergence investigation and the substantiation and construction of new algorithms on the base ...
A general approach to the determination of approximate solutions of general control problems by expl...
This paper deals with various approaches to solving optimization tasks. In prolog some examples from...
Creating or preparing Multi-objective formulations are a realistic models for many complex engineeri...
The new method of the continuous function minimization, based on the function continuous approximati...
Abstract:- Generalized algorithms for solving problems of discrete, integer, and Boolean programming...
The paper is aimed at the new numerical method development of the problem solution of the discrete a...
Some non-linear optimisation problems are difficult to solve by con-ventional hill-climbing methods,...
A coding of functions that allows a genetic algorithm to minimize functionals without analytic trial...
The numerical methods of solving of the random optimization problems were investigated with the aim ...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used ...
Optimization is a process that aims to find the best, most favorable, or most optimized solution for...
In this paper we apply one of approaches in category of heuristic methods as Genetic Algorithms for ...
Numerical methods of the non-stationary problem solution are investigated in the paper aiming at the...
The convergence investigation and the substantiation and construction of new algorithms on the base ...
A general approach to the determination of approximate solutions of general control problems by expl...
This paper deals with various approaches to solving optimization tasks. In prolog some examples from...
Creating or preparing Multi-objective formulations are a realistic models for many complex engineeri...
The new method of the continuous function minimization, based on the function continuous approximati...
Abstract:- Generalized algorithms for solving problems of discrete, integer, and Boolean programming...
The paper is aimed at the new numerical method development of the problem solution of the discrete a...
Some non-linear optimisation problems are difficult to solve by con-ventional hill-climbing methods,...
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