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Risk-Averse Anticipation for Dynamic Vehicle Routing

  • Marlin W. UlmerEmail author
  • Stefan Voß
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10079)

Abstract

In the field of dynamic vehicle routing, the importance to integrate stochastic information about possible future events in current decision making increases. Integration is achieved by anticipatory solution approaches, often based on approximate dynamic programming (ADP). ADP methods estimate the expected mean values of future outcomes. In many cases, decision makers are risk-averse, meaning that they avoid “risky” decisions with highly volatile outcomes. Current ADP methods in the field of dynamic vehicle routing are not able to integrate risk-aversion. In this paper, we adapt a recently proposed ADP method explicitly considering risk-aversion to a dynamic vehicle routing problem with stochastic requests. We analyze how risk-aversion impacts solutions’ quality and variance. We show that a mild risk-aversion may even improve the risk-neutral objective.

Keywords

Dynamic vehicle routing Anticipation Risk-aversion Approximate dynamic programming Stochastic customer requests 

References

  1. 1.
    Psaraftis, H.N., Wen, M., Kontovas, C.A.: Dynamic vehicle routing problems: three decades and counting. Networks 67(1), 3–31 (2016)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Ulmer, M.W., Mattfeld, D.C., Köster, F.: Budgeting time for dynamic vehicle routing with stochastic customer requests. Transp. Sci. (2016, to appear )Google Scholar
  3. 3.
    Powell, W.B., Towns, M.T., Marar, A.: On the value of optimal myopic solutions for dynamic routing and scheduling problems in the presence of user noncompliance. Transp. Sci. 34, 67–85 (2000)CrossRefzbMATHGoogle Scholar
  4. 4.
    Powell, W.B.: Approximate Dynamic Programming: Solving the Curses of Dimensionality. Wiley, New York (2011)CrossRefzbMATHGoogle Scholar
  5. 5.
    Dyer, J.S., Sarin, R.K.: Relative risk aversion. Manag. Sci. 28, 875–886 (1982)CrossRefzbMATHGoogle Scholar
  6. 6.
    Jackwerth, J.C.: Recovering risk aversion from option prices and realized returns. Rev. Financ. Stud. 13, 433–451 (2000)CrossRefGoogle Scholar
  7. 7.
    Adulyasak, Y., Jaillet, P.: Models and algorithms for stochastic and robust vehicle routing with deadlines. Transp. Sci. 50(2), 608–626 (2016)CrossRefGoogle Scholar
  8. 8.
    Lau, H.C., Yeoh, W., Varakantham, P., Nguyen, D.T., Chen, H.: Dynamic stochastic orienteering problems for risk-aware applications. In: Proceedings of the Conference on Uncertainty in Artificial Intelligence, pp. 448–458 (2012)Google Scholar
  9. 9.
    Taniguchi, E., Thompson, R.G., Yamada, T.: Incorporating risks in city logistics. Procedia-Soc. Behav. Sci. 2, 5899–5910 (2010)CrossRefGoogle Scholar
  10. 10.
    Jiang, D.R., Powell, W.B.: Approximate dynamic programming for dynamic quantile-based risk measures. Technical report, Princeton University (2015)Google Scholar
  11. 11.
    Puterman, M.L.: Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York (2014)zbMATHGoogle Scholar
  12. 12.
    Thomas, B.W.: Waiting strategies for anticipating service requests from known customer locations. Transp. Sci. 41, 319–331 (2007)CrossRefGoogle Scholar
  13. 13.
    Ruszczyński, A.: Risk-averse dynamic programming for Markov decision processes. Math. Program. 125, 235–261 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Rockafellar, R.T., Uryasev, S.: Optimization of conditional value-at-risk. J. Risk 2, 21–42 (2000)CrossRefGoogle Scholar
  15. 15.
    Ulmer, M.W., Mattfeld, D.C., Hennig, M., Goodson, J.C.: A rollout algorithm for vehicle routing with stochastic customer requests. In: Mattfeld, D., Spengler, T., Brinkmann, J., Grunewald, M. (eds.) Logistics Management. Lecture Notes in Logistics, pp. 217–227. Springer, Cham (2015). doi: 10.1007/978-3-319-20863-3_16 Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Technische Universität BraunschweigBraunschweigGermany
  2. 2.Universität HamburgHamburgGermany

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