Publication detail

Two-Stage Stochastic Programming for Transportation Network Design Problem

HRABEC, D. POPELA, P. ROUPEC, J. MAZAL, J. STODOLA, P.

Original Title

Two-Stage Stochastic Programming for Transportation Network Design Problem

English Title

Two-Stage Stochastic Programming for Transportation Network Design Problem

Type

conference paper

Language

en

Original Abstract

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.

English abstract

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.

Keywords

two-stage stochastic programming, scenario-based approach, transportation model, network design problem, genetic algorithm, hybrid algorithm

RIV year

2015

Released

08.07.2015

ISBN

978-3-319-19824-8

Book

Mendel 2015: Recent Advances in Soft Computing

Pages from

17

Pages to

25

Pages count

9

Documents

BibTex


@inproceedings{BUT115205,
  author="Dušan {Hrabec} and Pavel {Popela} and Jan {Roupec} and Jan {Mazal} and Petr {Stodola}",
  title="Two-Stage Stochastic Programming for Transportation Network Design Problem",
  annote="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.",
  booktitle="Mendel 2015: Recent Advances in Soft Computing",
  chapter="115205",
  doi="10.1007/978-3-319-19824-8_2",
  howpublished="print",
  number="1",
  year="2015",
  month="july",
  pages="17--25",
  type="conference paper"
}