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Параметрична декомпозиція багатоетапних транспортних моделей

Параметрична декомпозиція багатоетапних транспортних моделей

Abstract

Багатоетапні транспортні моделі займають особливе місце серед задач математичного програмуванні. При деталізованому підході до їх розв’язання, з описом елементарних актів управлінської діяльності, виникає проблема пошуку екстремуму алгоритмічної функції на безлічі алгоритмічних обмежень в умовах високої розмірності простору змінних. В таких випадках має сенс застосовувати параметричну декомпозицію, пов'язану з проблемами негладкої оптимізації опуклих функцій багатоетапних транспортних моделей. У статті розглянуто застосування алгоритму найшвидшого спуску для розв’язання таких задач. Flighted transport models occupy a special place among the problems of mathematical programming. With granular approach to their solution, describing the elementary acts of administrative activity, there arises the problem of the extremum of algorithmic functions on the set of algorithmic restrictions in the conditions of high dimensionality of the space of variables. Given that multi-stage transportation problem has a block structure with a small number of links, it makes sense to use such decomposition schemes that lead to the problem of minimizing nonsmooth convex piecewise-linear function of the related parameters, relevant constraints of the problem in a binder. The most promising and appropriate for solving such problems is the approximate analytical description of the object of management and development of approaches for solving the problem of finding an extremum algorithmic functions on the set of algorithmic constraints in high dimensional space of the variables of the problem and the limited time calculations. In such cases, it makes sense to use a parametric.

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Keywords

алгоритми, негладка оптимізація, градієнтні методи, block structure, виробничо-транспортне планування, onsmooth optimization, algorithms, gradient methods, багатоетапна транспортна модель, блокова структура

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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
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