Discrete Optimization Algorithm Based on Probability Distribution with Transformation of Target Values

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Publicat a:Programming and Computer Software vol. 50, no. 6 (Dec 2024), p. 445
Autor principal: Sarin, K. S.
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Springer Nature B.V.
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Accés en línia:Citation/Abstract
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024 7 |a 10.1134/S0361768824700312  |2 doi 
035 |a 3130548251 
045 2 |b d20241201  |b d20241231 
100 1 |a Sarin, K. S.  |u Tomsk State University of Control Systems and Radioelectronics, Tomsk, Russia (GRID:grid.440738.c) (ISNI:0000 0000 9460 4294) 
245 1 |a Discrete Optimization Algorithm Based on Probability Distribution with Transformation of Target Values 
260 |b Springer Nature B.V.  |c Dec 2024 
513 |a Journal Article 
520 3 |a Problems of search optimization in a discrete space, particularly, in a binary space where a variable can take only two values, are of great practical importance. This paper proposes a new population-based discrete optimization algorithm that uses probability distributions of variables. The distributions determine the probability of taking one or another discrete value and are generated by transforming target values of solutions into their weight coefficients. The performance of the algorithm is evaluated using unimodal and multimodal test functions with binary variables. The experimental results demonstrate the high efficiency of the proposed algorithm in terms of convergence rate and stability. 
653 |a Design 
653 |a Algorithms 
653 |a Probability 
653 |a Integer programming 
653 |a Embedded systems 
653 |a Methods 
653 |a Optimization algorithms 
653 |a Genetic algorithms 
653 |a Efficiency 
653 |a Optimization 
773 0 |t Programming and Computer Software  |g vol. 50, no. 6 (Dec 2024), p. 445 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
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