The DOI matches its Crossref record.
Decision Support for Consumer Direct Grocery Initiatives
Abstract
Many companies with consumer direct service models, especially grocery delivery services, have found that home delivery poses an enormous logistical challenge due to the unpredictability of demand coupled with strict delivery windows and low profit margin products. These systems have proven difficult to manage effectively and could benefit from new technology, particularly to manage the interaction between order capture and order delivery. In this article, we define routing and scheduling problems that incorporate important features of this emerging business model and propose algorithms, based on insertion heuristics, for their solution. In the proposed home delivery problem, the company decides which deliveries to accept or reject as well as the time slot for the accepted deliveries so as to maximize expected profits. Computational experiments reveal the importance of an approach that integrates order capture with order delivery and demonstrates the quality and value of the proposed algorithms.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
A review of dynamic vehicle routing problems
Pillac, V., Gendreau, M., Guéret, C., & Medaglia, A. L. (2013) · European Journal of Operational Research · doi:10.1016/j.ejor.2012.08.015 · Cited by 1,253
Dynamic vehicle routing problems: Three decades and counting
Psaraftis, H. N., Wen, M., & Kontovas, C. A. (2016) · Networks · doi:10.1002/net.21628 · Cited by 709
Lim, S. F. W. T., & Srai, J. S. (2018) · International Journal of Operations & Production Management · doi:10.1108/ijopm-12-2016-0733 · Cited by 92
Metadata
- Authors
- Campbell, A. M., & Savelsbergh, M. W. P.
- Venue
- Transportation Science
- Published
- 2005-08
- Volume
- 39
- Issue
- 3
- Pages
- 313-327
- ISSN
- 0041-1655 (ISSN-L)
- 1526-5447
- OpenAlex
- W2056755342
- Cited by
- 197
- References
- 0
- FWCI
- 26.18
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Decision Support for Consumer Direct Grocery Initiatives. https://app.cochat.ai/papers/10.1287/trsc.1040.0105
- The paper
- Campbell, A. M., & Savelsbergh, M. W. P. (2005). Decision Support for Consumer Direct Grocery Initiatives. Transportation Science. https://doi.org/10.1287/trsc.1040.0105
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.