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Proceedings of Higher Educational Institutions Маchine Building
Article . 2011
Data sources: CyberLeninka - Russian open access scientific library
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Методы адаптивного и генетического поиска в оперативном планировании производства

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2011 Russian Publisher:Федеральное государственное бюджетное образовательное учреждение высшего профессионального образования «Московский государственный технический университет имени Н.Э.Баумана»Journal:Известия высших учебных заведений. Машиностроение (issn: 0536-1044, Copyright policy )

Методы адаптивного и генетического поиска в оперативном планировании производства

Abstract

The article discusses the problems of the production scheduling process automation. A strict formulation of one practical scheduling problem is performed, the problems of its algorithmic complexity for scheduling are touched upon. The approaches to the problem to solve are proposed and investigated based on the artificial intelligence methods.

Рассмотрены проблемы автоматизации построения оперативных планов производства. Приведена формальная постановка одной практической задачи, затронуты вопросы ее алгоритмической сложности. Предложены и исследованы подходы к решению поставленной задачи на основе методов искусственного интеллекта.

Keywords

ОПЕРАТИВНОЕ ПЛАНИРОВАНИЕ ПРОИЗВОДСТВА, ТЕОРИЯ РАСПИСАНИЙ, NP-ПОЛНЫЕ ЗАДАЧИ, МЕТОДЫ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА, МУЛЬТИАГЕНТНЫЕ СИСТЕМЫ, АДАПТАЦИЯ ПРОГРАММНЫХ АГЕНТОВ, ГЕНЕТИЧЕСКИЕ АЛГОРИТМЫ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
bronze