
В статье рассматриваются гибридные схемы численного решения задач условной оптимизации, основанные на классических подходах, таких как метод штрафных функций, теория множителей Лагранжа, и метаэвристических алгоритмах. Приведён пример гибридной схемы, основанный на методе роя частиц и методе множителей Лагранжа с добавками. Представлены результаты численного эксперимента.
In the article hybrid methods of numerical solving constrained optimization problems based on classical approaches such as penalty functions method, Lagrange multipliers theory and metaheuristics are discussed. The example of hybrid method based on particle swarm optimization and augmented Lagrangian method is given. Numerical experiment results are provided.
№1(41) (2017)
metaheuristics, penalty functions, Lagrange multipliers, штрафные функции, метаэвристики, множители Лагранжа, условная оптимизация, constrained optimization
metaheuristics, penalty functions, Lagrange multipliers, штрафные функции, метаэвристики, множители Лагранжа, условная оптимизация, constrained optimization
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