Buffering locations in retail deliveries

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

This research helps a European retailer with its daily goods delivery operations. The challenge is the limited capacity of the transportation network in the Amsterdam area. This leads to very strict requirements for the delivery routing plans. In order to respond to this challenge both an analytical model and a numerical method are proposed. This method is capable of generating routing plans given all the necessary constraints including the cost structure. The model takes into account all incurred costs such as mileage, unsatisfied demand and waiting times; they all are weighted according to their relative importance. Furthermore, in order to reduce waiting times, buffering locations within the Amsterdam area are considered where a truck can park and wait until the loading zone at a store becomes available. The numerical method is approximate in nature and is based on the Column Generation technique. This technique allows iterative explorations of the search space by adding new promising one-truck routes (columns). The Regret construction heuristic is applied to generate an initial solution. New promising columns are generated by means of solving the Pricing Sub-problem which takes into account the duals of the Master problem relaxation. The analysis demonstrates that the buffers help to reduce the waiting times incurred by early arrivals without any drop in the total solution costs. Furthermore, a method is proposed to verify the usefulness of different buffering locations in the model.

Original languageEnglish
Pages (from-to)116-123
Number of pages8
JournalProcedia Computer Science
Volume151
Early online date21 May 2019
DOIs
Publication statusPublished - 2019
Event10th International Conference on Ambient Systems, Networks and Technologies, ANT 2019 and The 2nd International Conference on Emerging Data and Industry 4.0, EDI40 2019, Affiliated Workshops - Leuven, Belgium
Duration: 29 Apr 20192 May 2019

Fingerprint

Trucks
Costs
Numerical methods
Analytical models

Bibliographical note

Part of special issue: The 10th International Conference on Ambient Systems, Networks and Technologies (ANT 2019) / The 2nd International Conference on Emerging Data and Industry 4.0 (EDI40 2019) / Affiliated Workshops. Edited by Elhadi Shakshuki

Keywords

  • Column Generation
  • Dynamic Programming
  • Linear Programming
  • Local Search
  • Mathematical Optimization

Cite this

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title = "Buffering locations in retail deliveries",
abstract = "This research helps a European retailer with its daily goods delivery operations. The challenge is the limited capacity of the transportation network in the Amsterdam area. This leads to very strict requirements for the delivery routing plans. In order to respond to this challenge both an analytical model and a numerical method are proposed. This method is capable of generating routing plans given all the necessary constraints including the cost structure. The model takes into account all incurred costs such as mileage, unsatisfied demand and waiting times; they all are weighted according to their relative importance. Furthermore, in order to reduce waiting times, buffering locations within the Amsterdam area are considered where a truck can park and wait until the loading zone at a store becomes available. The numerical method is approximate in nature and is based on the Column Generation technique. This technique allows iterative explorations of the search space by adding new promising one-truck routes (columns). The Regret construction heuristic is applied to generate an initial solution. New promising columns are generated by means of solving the Pricing Sub-problem which takes into account the duals of the Master problem relaxation. The analysis demonstrates that the buffers help to reduce the waiting times incurred by early arrivals without any drop in the total solution costs. Furthermore, a method is proposed to verify the usefulness of different buffering locations in the model.",
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Buffering locations in retail deliveries. / Erkin, Dmitrii; Dugundji, Elenna; Koole, Ger; Gromicho, Joaquim; van der Mei, Rob.

In: Procedia Computer Science, Vol. 151, 2019, p. 116-123.

Research output: Contribution to JournalArticleAcademicpeer-review

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