Guidelines for the computational testing of machine learning approaches to vehicle routing problems
Luca Accorsi, Andrea Lodi, Daniele Vigo
| Year of publication: |
2022
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|---|---|
| Authors: | Accorsi, Luca ; Lodi, Andrea ; Vigo, Daniele |
| Published in: |
Operations research letters. - Amsterdam [u.a.] : Elsevier, ISSN 0167-6377, ZDB-ID 720735-9. - Vol. 50.2022, 2, p. 229-234
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| Subject: | Computational testing | Machine learning | Vehicle routing | Künstliche Intelligenz | Artificial intelligence | Tourenplanung | Vehicle routing problem | Computerunterstützung | Computerized method | Algorithmus | Algorithm | Theorie | Theory |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.orl.2022.01.018 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013192715