Two-Stage Stochastic Programming for Transportation Network Design Problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG42__%2F15%3A00531270" target="_blank" >RIV/60162694:G42__/15:00531270 - isvavai.cz</a>

Výsledek na webu

<a href="http://vavtest.unob.cz/registr" target="_blank" >http://vavtest.unob.cz/registr</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-19824-8_2" target="_blank" >10.1007/978-3-319-19824-8_2</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Two-Stage Stochastic Programming for Transportation Network Design Problem

Popis výsledku v původním jazyce

The transportation network design problem is a well-known optimization problem with many practical applications. This paper deals with demand-based applications, where the operational as well as many other decisions are often made under uncertainty. Capturing the uncertain demand by using scenario-based approach, we formulate the two-stage stochastic mixed-integer linear problem, where the decision, which is made under uncertainty, of the first-stage program, is followed by the second-stage decision that reacts to the observed demand. Such a program may reach solvability limitations of algorithms for large scale real world data, so we refer to the so-called hybrid algorithm that combines a traditional optimization algorithm and a suitable genetic algorithm. The obtained results are presented in an explanatory form with the use of a sequence of figures.

Název v anglickém jazyce

Two-Stage Stochastic Programming for Transportation Network Design Problem

Popis výsledku anglicky

The transportation network design problem is a well-known optimization problem with many practical applications. This paper deals with demand-based applications, where the operational as well as many other decisions are often made under uncertainty. Capturing the uncertain demand by using scenario-based approach, we formulate the two-stage stochastic mixed-integer linear problem, where the decision, which is made under uncertainty, of the first-stage program, is followed by the second-stage decision that reacts to the observed demand. Such a program may reach solvability limitations of algorithms for large scale real world data, so we refer to the so-called hybrid algorithm that combines a traditional optimization algorithm and a suitable genetic algorithm. The obtained results are presented in an explanatory form with the use of a sequence of figures.

Druh

D - Stať ve sborníku

CEP obor

KA - Vojenství

OECD FORD obor

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Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances in Intelligent Systems and Computing, Vol. 378

ISBN

978-3-319-19823-1

ISSN

—

e-ISSN

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Počet stran výsledku

9

Strana od-do

17-25

Název nakladatele

Springer International Publishing Switzerland

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

7. 6. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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