Publication result detail

Waste processing facility location problem by stochastic programming: Models and solutions

POPELA, P.; HRABEC, D.; KŮDELA, J.; ŠOMPLÁK, R.; PAVLAS, M.; ROUPEC, J.; NOVOTNÝ, J.

Original Title

Waste processing facility location problem by stochastic programming: Models and solutions

English Title

Waste processing facility location problem by stochastic programming: Models and solutions

Type

Paper in proceedings (conference paper)

Original Abstract

The paper deals with the so-called waste processing facility location problem (FLP), which asks for establishing a set of operational waste processing units, optimal against the total expected cost. We minimize the waste management (WM) expenditure of the waste producers, which is derived from the related waste processing, transportation, and investment costs. We use a stochastic programming approach in recognition of the inherent uncertainties in this area. Two relevant models are presented and discussed in the paper. Initially, we extend the common transportation network flow model with on-and-off waste-processing capacities in selected nodes, representing the facility location. Subsequently, we model the randomly-varying production of waste by a scenario-based two-stage stochastic integer linear program. Finally, we employ selected pricing ideas from revenue management to model the behavior of the waste producers, who we assume to be environmentally friendly. The modeling ideas are illustrated on an example of limited size solved in GAMS. Computations on larger instances were realized with traditional and heuristic algorithms, implemented within MATLAB.

English abstract

The paper deals with the so-called waste processing facility location problem (FLP), which asks for establishing a set of operational waste processing units, optimal against the total expected cost. We minimize the waste management (WM) expenditure of the waste producers, which is derived from the related waste processing, transportation, and investment costs. We use a stochastic programming approach in recognition of the inherent uncertainties in this area. Two relevant models are presented and discussed in the paper. Initially, we extend the common transportation network flow model with on-and-off waste-processing capacities in selected nodes, representing the facility location. Subsequently, we model the randomly-varying production of waste by a scenario-based two-stage stochastic integer linear program. Finally, we employ selected pricing ideas from revenue management to model the behavior of the waste producers, who we assume to be environmentally friendly. The modeling ideas are illustrated on an example of limited size solved in GAMS. Computations on larger instances were realized with traditional and heuristic algorithms, implemented within MATLAB.

Keywords

Waste processing; Facility location problem; Stochastic programming; Two decision stages; Uncertainty modeling; Scenarios; Mathematical programming algorithms; Heuristics; Genetic algorithms; GAMS; MATLAB; Pricing related ideas

Key words in English

Waste processing; Facility location problem; Stochastic programming; Two decision stages; Uncertainty modeling; Scenarios; Mathematical programming algorithms; Heuristics; Genetic algorithms; GAMS; MATLAB; Pricing related ideas

Authors

POPELA, P.; HRABEC, D.; KŮDELA, J.; ŠOMPLÁK, R.; PAVLAS, M.; ROUPEC, J.; NOVOTNÝ, J.

RIV year

2019

Released

05.08.2018

Publisher

Springer Nature

Location

Switzerland

ISBN

9783319978871

Book

Advances in Intelligent Systems and Computing

ISBN

2194-5357

Periodical

Advances in Intelligent Systems and Computing

Volume

837

Number

1

State

Swiss Confederation

Pages from

167

Pages to

179

Pages count

13

URL

https://link.springer.com/chapter/10.1007/978-3-319-97888-8_15

BibTex

@inproceedings{BUT151989,
  author="POPELA, P. and HRABEC, D. and KŮDELA, J. and ŠOMPLÁK, R. and PAVLAS, M. and ROUPEC, J. and NOVOTNÝ, J.",
  title="Waste processing facility location problem by stochastic programming: Models and solutions",
  booktitle="Advances in Intelligent Systems and Computing",
  year="2018",
  journal="Advances in Intelligent Systems and Computing",
  volume="837",
  number="1",
  pages="167--179",
  publisher="Springer Nature",
  address="Switzerland",
  doi="10.1007/978-3-319-97888-8\{_}15",
  isbn="9783319978871",
  issn="2194-5357",
  url="https://link.springer.com/chapter/10.1007/978-3-319-97888-8_15"
}