Publication detail

Using Genetic Algorithm for Advanced Municipal Waste Collection in Smart City

FUJDIAK, R. MAŠEK, P. OLSHANNIKOVA, E. MLÝNEK, P. MIŠUREC, J.

Original Title

Using Genetic Algorithm for Advanced Municipal Waste Collection in Smart City

Type

conference paper

Language

English

Original Abstract

The Internet of Things (IoT), as expected infrastructure for envisioned concept of Smart City, brings new possibilities for the city management. IoT vision introduces promising and economical solutions for massive data collection and its analysis which can be applied in many domains and so make them operating more efficiently. In this paper, we are discussing one of the most challenging issues - municipal waste-collection within the Smart City. To optimize the logistic procedure of waste collection, we use own genetic algorithm implementation. The presented solution provides calculation of more efficient garbage-truck routes. As an output, we provide a set of simulations focused on mentioned area. All our algorithms are implemented within the integrated simulation framework which is developed as an open source solution with respect to future modifications.

Keywords

Smart City; Waste management; Genetic Algorithm; Optimization; Simulation

Authors

FUJDIAK, R.; MAŠEK, P.; OLSHANNIKOVA, E.; MLÝNEK, P.; MIŠUREC, J.

Released

22. 7. 2016

ISBN

978-1-5090-2525-1

Book

Proceedings of the 10th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2016

Pages from

1

Pages to

6

Pages count

6

URL

https://ieeexplore.ieee.org/document/7574016

BibTex

@inproceedings{BUT126942,
  author="FUJDIAK, R. and MAŠEK, P. and OLSHANNIKOVA, E. and MLÝNEK, P. and MIŠUREC, J.",
  title="Using Genetic Algorithm for Advanced Municipal Waste Collection in Smart City",
  booktitle="Proceedings of the 10th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2016",
  year="2016",
  pages="1--6",
  doi="10.1109/CSNDSP.2016.7574016",
  isbn="978-1-5090-2525-1",
  url="https://ieeexplore.ieee.org/document/7574016"
}