Skip to main content
Log in

Optimal balanced chain decomposition of partially ordered sets with applications to operating cost minimization in aircraft routing problems

  • Original Research
  • Published:
Public Transport Aims and scope Submit manuscript

Abstract

We consider the task of constructing a cost-effective daily flight schedule with a minimum number of required aircrafts and a maximum number of balanced flight routes, namely, routes with the same start and end spatial location. We suggest a solution strategy which is able to determine the problem’s hardness by estimating the number of all flight plans with a minimum number of required aircrafts. Provided that this number is not too large, the same algorithm is utilized for fully enumerating and detecting the set of solutions that have the maximum number of balanced routes. Our experimental study implies that the method is both effective and scalable in practice. For example, when applied to the Australian domestic flights timetable which is serviced by a total of eighty-eight aircrafts, our method manages to increase the number of balanced flight routes from nine to forty-two, while using only several minutes of computational time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

Software packages and the research data is available on the author’s website under: https://people.smp.uq.edu.au/RadislavVaisman/sw/scheduling/software.zip

References

  • Ahmed MB, Mansour FZ, Haouari M (2018) Robust integrated maintenance aircraft routing and crew pairing. J Air Transp Manag 73:15–31

    Article  Google Scholar 

  • Arnold F, Gendreau M, Sörensen K (2019) Efficiently solving very large-scale routing problems. Comput Oper Res 107:32–42

    Article  Google Scholar 

  • Asmussen S, Glynn P (2007) Stochastic Simulation: Algorithms and Analysis. Stochastic Modelling and Applied Probability, vol 57. Springer, New York

    Book  Google Scholar 

  • Bertelé U, Brioschi F (1969) Contribution to nonserial dynamic programming. J Math Anal Appl 28(2):313–325

    Article  Google Scholar 

  • Broder A (1986) How hard is it to marry at random? (On the approximation of the permanent). In: Proceedings of the eighteenth annual ACM symposium on theory of computing, STOC ’86, pp. 50–58. ACM

  • Ceder A, Stern HI (1981) Deficit function bus scheduling with deadheading trip insertions for fleet size reduction. Transp Sci 15(4):338–363

    Article  Google Scholar 

  • Cortes JD, Suzuki Y (2020) Vehicle routing with shipment consolidation. Int J Prod Econ 227:107–120

    Article  Google Scholar 

  • Curticapean R, Dell H, Fomin F, Goldberg LA, Lapinskas J (2019) A fixed-parameter perspective on #BIS. Algorithmica 81:3844–3864

    Article  Google Scholar 

  • Dilworth RP (1950) A decomposition theorem for partially ordered sets. Annal Math 51:161–166

    Article  Google Scholar 

  • Dyer M, Goldberg LA, Greenhill C, Jerrum M (2004) The relative complexity of approximate counting problems. Algorithmica 38:471–500

    Article  Google Scholar 

  • Fulkerson DR (1956) Note on Dilworth’s decomposition theorem for partially ordered sets. Proc Am Math Soc 7:701–702

    Google Scholar 

  • Goldreich O (2008) Computational complexity: a conceptual perspective. ACM SIGACT News 39(3):35–39

    Article  Google Scholar 

  • Hopcroft JE, Karp RM (1973) An \(n^{5/2}\) algorithm for maximum matchings in bipartite graphs. SIAM J Comput. 2(4):225–231

    Article  Google Scholar 

  • Knuth DE (1975) Estimating the efficiency of backtrack programs. Math Comput 29(129):122–136

    Article  Google Scholar 

  • Lan S, Clarke JP, Barnhart C (2006) Planning for robust airline operations: Optimizing aircraft routings and flight departure times to minimize passenger disruptions. Transp Sci 40(1):15–28

    Article  Google Scholar 

  • Lei Z, Zhe L, Chun-An C, Wanpracha Art C (2020) Airline planning and scheduling: Models and solution methodologies. Front Eng Manag 7:1–26

    Article  Google Scholar 

  • Liu T, Ceder A (2017) Deficit function related to public transport: 50 year retrospective, new developments, and prospects. Transp Res Part B Methodol 100:1–19

    Article  Google Scholar 

  • Marla L, Vaze V, Barnhart C (2018) Robust optimization: Lessons learned from aircraft routing. Comput Oper Res 98:165–184

    Article  Google Scholar 

  • Nasibov E, Eliiyi U, Ertac MO, Kuvvetli U (2013) Deadhead trip minimization in city bus transportation: A real life application. Promet Traffic Transp 25(2):137–145

    Google Scholar 

  • Provan JS, Ball MO (1983) The complexity of counting cuts and of computing the probability that a graph is connected. SIAM J Comput 12:777–788

    Article  Google Scholar 

  • Rubinstein RY, Ridder A, Vaisman R (2013) Fast Sequential Monte Carlo Methods for Counting and Optimization. John Wiley & Sons, New York

    Book  Google Scholar 

  • Simovici DA, Djeraba C (2014) Mathematical Tools for Data Mining: Set Theory. Partial Orders. Combinatorics. Advanced Information and Knowledge Processing, Springer, London

    Book  Google Scholar 

  • Sinclair AJ (1988) Randomised algorithms for counting and generating combinatorial structures, PhD thesis, University of Edinburgh

  • Stern HI, Gertsbakh IB (2019) Using deficit functions for aircraft fleet routing. Oper Res Perspect 6:100–104

    Google Scholar 

  • Stojković G, Soumis F, Desrosiers J, Solomon MM (2002) An optimization model for a real-time flight scheduling problem. Transp Res Part A Policy Pract 36(9):779–788

    Article  Google Scholar 

  • Vaisman R, Kroese DP (2017) Stochastic enumeration method for counting trees. Methodol Comput Appl Probab 19(1):31–73

    Article  Google Scholar 

  • Vaisman R, Kroese DP, Gertsbakh IB (2016) Improved sampling plans for combinatorial invariants of coherent systems. IEEE Trans Reliabil 65(1):410–424

    Article  Google Scholar 

  • Valiant LG (1979) The complexity of enumeration and reliability problems. SIAM J Comput 8(3):410–421

    Article  Google Scholar 

  • Vazirani VV (2003) Approximation algorithms. Springer, Berlin

    Book  Google Scholar 

Download references

Acknowledgements

We are thoroughly grateful to the anonymous reviewers for their valuable and constructive remarks and suggestions. This paper is dedicated to the memory of Professor Ilya B. Gertsbakh (1933–2020). This work was supported by the Australian Research Council Centre of Excellence for Mathematical & Statistical Frontiers, under CE140100049 grant number.

Funding

Centre of Excellence for Electromaterials Science, Australian Research Council (AU) (Grant no. CE140100049).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Radislav Vaisman.

Ethics declarations

Conflict of interest

We confirm that we are not aware of any conflict of interest for this study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendices

A The F30 timetable from Stern and Gertsbakh (2019)

Table 3 The F30 flight timetable with 30 passages. For each passage, the table displays the flight number, the departure and the arrival terminals, and the departure and the arrival times. Here, a fraction such as 4.5 in the first row, stands for the 4:30AM time

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vaisman, R., Gertsbakh, I.B. Optimal balanced chain decomposition of partially ordered sets with applications to operating cost minimization in aircraft routing problems. Public Transp 15, 199–225 (2023). https://doi.org/10.1007/s12469-022-00304-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12469-022-00304-5

Keywords

Navigation