Hybrid system modeling and operation schedule optimization for gas transportation network based on combined method of DE, GA and hybrid petri net

Evgeny Malamura, Tomohiro Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

We present an integrated Differential Evolution (DE), Genetic Algorithm (GA) and Hybrid Petri net (HPN) based approach for scheduling of a hybrid dynamical transport network operation. The main advantage of the proposed approach is a reduction of complexity in the optimization problem formulation for a system with non-linear constraints and hybrid discretecontinuous parameters and the impact of discontinuities of the search space ensued by autonomous switching of the network components. In particular the scheduling problem for a natural gas compressor station with parallel pumps is addressed in the case-study.

Original languageEnglish
Title of host publicationProceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1032-1035
Number of pages4
ISBN (Electronic)9781467389853
DOIs
Publication statusPublished - 2016 Aug 31
Event5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 - Kumamoto, Japan
Duration: 2016 Jul 102016 Jul 14

Other

Other5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016
CountryJapan
CityKumamoto
Period16/7/1016/7/14

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Keywords

  • Differential Evolution
  • Gas Transport Networks
  • Genetic Algorithm
  • Hybrid Systems
  • Petri Net

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Cite this

Malamura, E., & Murata, T. (2016). Hybrid system modeling and operation schedule optimization for gas transportation network based on combined method of DE, GA and hybrid petri net. In Proceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 (pp. 1032-1035). [7557765] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IIAI-AAI.2016.106