Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,179

The DOI matches its Crossref record.

A Heuristic Algorithm for the Vehicle-Dispatch Problem

Gillett, Billy E., Miller, Leland R.·1974·Operations Research

Abstract

This paper introduces and illustrates an efficient algorithm, called the sweep algorithm, for solving medium- as well as large-scale vehicle-dispatch problems with load and distance constraints for each vehicle. The locations that are used to make up each route are determined according to the polar-coordinate angle for each location. An iterative procedure is then used to improve the total distance traveled over all routes. The algorithm has the feature that the amount of computation required increases linearly with the number of locations if the average number of locations for each route remains relatively constant. For example, if the average number of locations per route is 7.5, the algorithm takes approximately 75 seconds to solve a 75-location problem on an IBM 360/67 and approximately 115 seconds to solve a 100-location problem. In contrast, the time to solve a problem with a fixed number of locations increases quadratically with the average number of locations per route. The sweep algorithm generally produces results that are significantly better than those produced by Gaskell's savings approach and are generally slightly better than Christofides and Eilon's results; however, the sweep algorithm is not as computationally efficient as Gaskell's and is slightly less so than Christofides and Eilon's.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1287/opre.22.2.340

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.

A few free checks a day · papers already verified open instantly · results are public

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

See all 1,179

Metadata

Authors
Gillett, B. E., & Miller, L. R.
Venue
Operations Research
Published
1974-04
Volume
22
Issue
2
Pages
340-349
ISSN
  • 0030-364X (ISSN-L)
  • 1526-5463
OpenAlex
W2108753073
Cited by
1,179
References
0
FWCI
72.84
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: A Heuristic Algorithm for the Vehicle-Dispatch Problem. https://app.cochat.ai/papers/10.1287/opre.22.2.340
The paper
Gillett, B. E., & Miller, L. R. (1974). A Heuristic Algorithm for the Vehicle-Dispatch Problem. Operations Research. https://doi.org/10.1287/opre.22.2.340

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.