Skip to main content

An Optimization Approach to the Ordering Phase of an Attended Home Delivery Service

  • Conference paper
  • First Online:
Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2019)

Abstract

Attended Home Delivery (AHD) systems are used whenever a supplying company offers online shopping services which require that customers must be present when their deliveries arrive. Therefore, the supplying company and the customer must both agree on a time window, which ideally is rather short, during which delivery is guaranteed. Typically, a capacitated Vehicle Routing Problem with Time Windows forms the underlying optimization problem of the AHD system. In this work we consider an AHD system that runs the online grocery shopping service of an international grocery retailer.

The ordering phase, during which customers place their orders through the web service, is the computationally most challenging part of the AHD system. The delivery schedule must be build dynamically as new orders are placed. We propose a solution approach that allows to determine which delivery time windows can be offered to potential customers. We split the computations of the ordering phase into four key steps. For performing these basic steps we suggest both a heuristic approach and a hybrid approach employing Mixed-Integer Linear Programs. In an experimental evaluation we demonstrate the efficiency of our approaches.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

  1. Agatz, N., Campbell, A.M., Fleischmann, M., Savelsbergh, M.W.P.: Challenges and opportunities in attended home delivery. In: Golden, B., Raghavan, S., Wasil, E. (eds.) The Vehicle Routing Problem: Latest Advances and New Challenges, pp. 379–396. Springer, US (2008). https://doi.org/10.1007/978-0-387-77778-8_17

    Chapter  Google Scholar 

  2. Campbell, A.M., Savelsbergh, M.W.P.: Decision support for consumer direct grocery initiatives. Transp. Sci. 39(3), 313–327 (2005)

    Article  Google Scholar 

  3. Ehmke, J.F.: Attended home delivery. In: Integration of Information and Optimization Models for Routing in City Logistics, pp. 23–33. Springer, Boston (2012). https://doi.org/10.1007/978-1-4614-3628-7_3

    Chapter  Google Scholar 

  4. Ehmke, J.F., Campbell, A.M.: Customer acceptance mechanisms for home deliveries in metropolitan areas. Eur. J. Oper. Res. 233(1), 193–207 (2014). https://doi.org/10.1016/j.ejor.2013.08.028

    Article  Google Scholar 

  5. El-Sherbeny, N.A.: Vehicle routing with time windows: an overview of exact heuristic and metaheuristic methods. J. King Saud Univ. 22, 123–131 (2010)

    Article  Google Scholar 

  6. Gendreau, M., Hertz, A., Laporte, G., Stan, M.: A generalized insertion heuristic for the traveling salesman problem with time windows. Oper. Res. 46(3), 330–335 (1998)

    Article  Google Scholar 

  7. Hungerländer, P., Maier, K., Pöcher, J., Rendl, A., Truden, C.: Solving an on-line capacitated vehicle routing problem with structured time windows. In: Fink, A., Fügenschuh, A., Geiger, M.J. (eds.) Operations Research Proceedings 2016. ORP, pp. 127–132. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-55702-1_18

    Chapter  Google Scholar 

  8. Hungerländer, P., Rendl, A., Truden, C.: On the slot optimization problem in on-line vehicle routing. Transp. Res. Procedia 27, 492–499 (2017). https://doi.org/10.1016/j.trpro.2017.12.046

    Article  Google Scholar 

  9. Hungerländer, P., Truden, C.: Efficient and easy-to-implement mixed-integer linear programs for the traveling salesperson problem with time windows. Transp. Res. Procedia 30, 157–166 (2018). https://doi.org/10.1016/j.trpro.2018.09.018. EURO Mini Conference on “Advances in Freight Transportation and Logistics”

    Article  Google Scholar 

  10. Klein, R., Mackert, J., Neugebauer, M., Steinhardt, C.: A model-based approximation of opportunity cost for dynamic pricing in attended home delivery. OR Spectrum (2017). https://doi.org/10.1007/s00291-017-0501-3

  11. Klein, R., Neugebauer, M., Ratkovitch, D., Steinhardt, C.: Differentiated time slot pricing under routing considerations in attended home delivery. Transp. Sci. (2017). https://doi.org/10.1287/trsc.2017.0738

    Article  Google Scholar 

  12. Köhler, C., Ehmke, J.F., Campbell, A.M.: Flexible time window management for attended home deliveries. Omega (2019). https://doi.org/10.1016/j.omega.2019.01.001

    Article  Google Scholar 

  13. Lenstra, J.K., Kan, A.H.G.R.: Complexity of vehicle routing and scheduling problems. Networks 11(2), 221–227 (1981). https://doi.org/10.1002/net.3230110211

    Article  Google Scholar 

  14. Pan, S., Giannikas, V., Han, Y., Grover-Silva, E., Qiao, B.: Using customer-related data to enhance e-grocery home delivery. Ind. Manag. Data Syst. 117(9), 1917–1933 (2017). https://doi.org/10.1108/IMDS-10-2016-0432

    Article  Google Scholar 

  15. Solomon, M.M.: Algorithms for the vehicle routing and scheduling problems with time window constraints. Oper. Res. 35(2), 254–265 (1987). https://doi.org/10.1287/opre.35.2.254

    Article  MathSciNet  MATH  Google Scholar 

  16. Syndy: The state of online grocery retail in Europe 2015 (2015). http://www.syndy.com/report-the-state-of-online-grocery-retail-2015/

  17. Vienna public transport (Wiener Linien): 2017 - Facts and Figures (2018). https://www.wienerlinien.at/media/files/2018/facts_and_figures_2017_243486.pdf

  18. Yang, X., Strauss, A.K., Currie, C.S.M., Eglese, R.: Choice-based demand management and vehicle routing in E-fulfillment. Transp. Sci. 50(2), 473–488 (2016)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christian Truden .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Cwioro, G., Hungerländer, P., Maier, K., Pöcher, J., Truden, C. (2019). An Optimization Approach to the Ordering Phase of an Attended Home Delivery Service. In: Rousseau, LM., Stergiou, K. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2019. Lecture Notes in Computer Science(), vol 11494. Springer, Cham. https://doi.org/10.1007/978-3-030-19212-9_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-19212-9_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19211-2

  • Online ISBN: 978-3-030-19212-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics