Solving general convex quadratic multi-objective optimization problems via a projection neurodynamic model

A neural network model is constructed to solve convex quadratic multi-objective programming problem (CQMPP). The CQMPP is first converted into an equivalent single-objective convex quadratic programming problem by the mean of the weighted sum method, where the Pareto optimal solution (POS) are given...

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Vydané v:	Cognitive neurodynamics Ročník 18; číslo 4; s. 2095 - 2110
Hlavní autori:	Jahangiri, Mohammadreza, Nazemi, Alireza
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Dordrecht Springer Netherlands 01.08.2024 Springer Nature B.V
Predmet:	Algorithms Approximation Artificial Intelligence Biochemistry Biomedical and Life Sciences Biomedicine Cognitive Psychology Computer Science Dynamical systems Equilibrium Integer programming Linear programming Mathematical programming Methods Multiple objective analysis Neural networks Neurosciences Optimization Ordinary differential equations Pareto optimization Pareto optimum Quadratic programming Research Article Pareto optimal solution Stability Convex quadratic programming problem Neural networks Multi-objective optimization problem Convergence
ISSN:	1871-4080, 1871-4099
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