Metaheuristics for Natural Gas Pipeline Networks

Roger Z. Ríos-Mercado ()
Additional contact information
Roger Z. Ríos-Mercado: Universidad Autónoma de Nuevo León (UANL), Graduate Program in Systems Engineering

Chapter 37 in Handbook of Heuristics, 2018, pp 1103-1121 from Springer

Abstract: Abstract In this chapter an overview of metaheuristic algorithms that have been very successful in tackling a particular class of natural gas pipeline network optimization problems is presented. In particular, the problem of minimizing fuel consumption incurred by the compressor stations driving natural gas in pipeline networks is addressed. This problem has been studied from different angles over the past few years by virtue of its tremendous economical impact. First, a general mathematical framework for this class of problems is presented. After establishing the most relevant model properties and fundamental network topologies, which are key factors for choosing an appropriate solution technique, current state-of-the-art metaheuristics are presented for handling different versions of this problem. This work concludes by highlighting the most relevant and important challenges of this very exciting area of research in natural gas transportation networks.

Keywords: Natural gas transmission systems; Pipeline optimization; Nonlinear programming; Mixed-integer nonlinear programming; Tabu search; Ant colony optimization; Simulated annealing; Particle swarm optimization (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-07124-4_51

Ordering information: This item can be ordered from
http://www.springer.com/9783319071244

DOI: 10.1007/978-3-319-07124-4_51

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().