Heuristics and Meta-heuristics for Runway Scheduling Problems

Farbod Farhadi ()
Additional contact information
Farbod Farhadi: Roger Williams University

Chapter Chapter 8 in Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling, 2016, pp 141-163 from Springer

Abstract: Abstract This chapter addresses the state-of-the-art heuristic and meta-heuristic approaches for solving aircraft runway scheduling problem under variety of settings. Runway scheduling has been one of the emerging challenges in air traffic control as the congestion figures continue to rise. From a modeling point of view, mixed-integer programming formulations for single and multiple dependent and independent runways are presented. A set partitioning reformulation of the problem is demonstrated which suggests development of a column generation scheme. From a solution methodology viewpoint, generic heuristic algorithms, optimization-based approaches, and a dynamic programming scheme within the column generation algorithm are presented. Common meta-heuristic approaches that model variant problem settings under static and dynamic environments are discussed.

Keywords: Runway scheduling; Mixed-integer programming; Dynamic programming; Optimization-based heuristics; Meta-heuristics (search for similar items in EconPapers)
Date: 2016
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:isochp:978-3-319-26024-2_8

Ordering information: This item can be ordered from
http://www.springer.com/9783319260242

DOI: 10.1007/978-3-319-26024-2_8

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().