Skip to main content
SpringerLink
Log in

State-of-the-Art Solution Techniques for OP and TOP

  • Chapter
  • First Online:
Orienteering Problems

Part of the book series: EURO Advanced Tutorials on Operational Research ((EUROATOR))

Abstract

Definitions and mathematical models of the OP and the TOP were introduced in Chaps. 2 and 3. In this chapter, we will discuss the benchmark instances and state-of-the-art solution techniques for both OP and TOP. Some illustrations of benchmark instances and solutions are included in order to increase the understanding in the difficulty of solving this problem and to provide additional insights. The solution techniques are classified into two different categories: exact approaches and (meta)heuristic techniques.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 84.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Bianchessi N, Mansini R, Speranza MG (2018) A branch-and-cut algorithm for the team orienteering problem. Int Trans Oper Res 25:627–635

    Article  MathSciNet  MATH  Google Scholar 

  • Bouly H, Dang DC, Moukrim A (2010) A memetic algorithm for the team orienteering problem. 4OR 8(1):49–70

    Google Scholar 

  • Boussier S, Feillet D, Gendreau M (2007) An exact algorithm for the team orienteering problem. 4OR 5(3):211–230

    Google Scholar 

  • Butt SE, Ryan DM (1999) An optimal solution procedure for the multiple tour maximum collection problem using column generation. Comput Oper Res 26(4):427–441

    Article  MathSciNet  MATH  Google Scholar 

  • Campos V, Martí R, Sánchez-Oro J, Duarte A (2014) GRASP with path relinking for the orienteering problem. J Oper Res Soc 65(12):1800–1813

    Article  Google Scholar 

  • Chao IM, Golden BL, Wasil EA (1996a) A fast and effective heuristic for the orienteering problem. Eur J Oper Res 88(3):475–489

    Article  MATH  Google Scholar 

  • Chao IM, Golden BL, Wasil EA (1996b) The team orienteering problem. Eur J Oper Res 88(3):464–474

    Article  MATH  Google Scholar 

  • Dang DC, El-Hajj R, Moukrim A (2013a) A branch-and-cut algorithm for solving the team orienteering problem. In: Gomes C, Sellmann M (eds) Integration of AI and OR techniques in constraint programming for combinatorial optimization problems, vol 7874. Lecture Notes in Computer Science. Springer, pp 332–339

    Google Scholar 

  • Dang DC, Guibadj RN, Moukrim A (2013b) An effective PSO-inspired algorithm for the team orienteering problem. Eur J Oper Res 229(2):332–344

    Article  MATH  Google Scholar 

  • Feillet D, Dejax P, Gendreau M (2005) Traveling salesman problems with profits. Transp Sci 39(2):188–205

    Article  Google Scholar 

  • Fischetti M, Salazar-González JJ, Toth P (1998) Solving the orienteering problem through branch-and-cut. INFORMS J Comput 10:133–148

    Article  MathSciNet  MATH  Google Scholar 

  • Gunawan A, Lau HC, Vansteenwegen P (2016) Orienteering problem: a survey of recent variants, solution approaches and applications. Eur J Oper Res 255(2):315–332

    Article  MathSciNet  MATH  Google Scholar 

  • Ke L, Zhai L, Li J, Chan FTS (2016) Pareto mimic algorithm: an approach to the team orienteering problem. Omega 61:155–166

    Article  Google Scholar 

  • Keshtkaran M, Ziarati K, Bettinelli A, Vigo D (2015) Enhanced exact solution methods for the team orienteering problem. Int J Prod Res 1–11

    Google Scholar 

  • Kobeaga G, Merino M, Lozano JA (2018) An efficient evolutionary algorithm for the orienteering problem. Comput Oper Res 90:42–59

    Article  MathSciNet  MATH  Google Scholar 

  • Lin SW (2013) Solving the team orienteering problem using effective multi-start simulated annealing. Appl Soft Comput 13(2):1064–1073

    Article  Google Scholar 

  • Marinakis Y, Politis M, Marinaki M, Matsatsinis N (2015) A memetic-GRASP algorithm for the solution of the orienteering problem. In: Le Thi HA, Dinh TP, Nguyen NT (eds) Modelling, computation and optimization in information systems and management sciences, Advances in intelligent systems and computing, vol 360. Springer, pp 105–116

    Google Scholar 

  • Poggi M, Viana H, Uchoa E (2010) The team orienteering problem: formulations and branch-cut and price. In: Erlebach T, Lübbecke M (eds) 10th workshop on algorithmic approaches for transportation modelling, optimization, and systems (ATMOS’10), Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, OpenAccess Series in Informatics (OASIcs), vol 14, pp 142–155

    Google Scholar 

  • Santini A (2019) An adaptive large neighbourhood search algorithm for the orienteering problem. Expert Syst Appl 123(1):154–167

    Article  Google Scholar 

  • Sevkli Z, Sevilgen FE (2010a) Discrete particle swarm optimization for the orienteering problem. In: Proceedings of the IEEE congress on evolutionary computation (CEC 2010). Barcelona, Spain, pp 3234–3241, 18–23 July 2010

    Google Scholar 

  • Sevkli Z, Sevilgen FE (2010b) StPSO: Strengthened particle swarm optimization. Turk J Electr Eng Comput Sci 18(6):1095–1114

    Google Scholar 

  • Tsiligirides T (1984) Heuristic methods applied to orienteering. J Oper Res Soc 35(9):797–809

    Article  Google Scholar 

  • Vansteenwegen P, Souffriau W, Van Oudheusden D (2011a) The orienteering problem: a survey. Eur J Oper Res 209(1):1–10

    Article  MathSciNet  MATH  Google Scholar 

  • Vansteenwegen P, Souffriau W, Vanden Berghe G, Van Oudheusden D (2011b) The city trip planner: an expert system for tourists. Expert Syst Appl 38(6):6540–6546

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. KU Leuven Mobility Research Centre, University of Leuven, Leuven, Belgium

    Pieter Vansteenwegen

  2. School of Information Systems, Singapore Management University, Singapore, Singapore

    Aldy Gunawan

Authors
  1. Pieter Vansteenwegen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aldy Gunawan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pieter Vansteenwegen .

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Vansteenwegen, P., Gunawan, A. (2019). State-of-the-Art Solution Techniques for OP and TOP. In: Orienteering Problems. EURO Advanced Tutorials on Operational Research. Springer, Cham. https://doi.org/10.1007/978-3-030-29746-6_5

Download citation

Publish with us

Policies and ethics

Search

Navigation