Publication: The Electric Home Health Care Routing and Scheduling Problem with Time Windows and Fast Chargers
| dc.authorscopusid | 57189599254 | |
| dc.authorscopusid | 56399128200 | |
| dc.authorscopusid | 24773991000 | |
| dc.contributor.author | Erdem, Mehmet | |
| dc.contributor.author | Koç, Ç. | |
| dc.contributor.author | Yücel, E. | |
| dc.date.accessioned | 2025-12-11T00:29:45Z | |
| dc.date.issued | 2022 | |
| dc.department | Ondokuz Mayıs Üniversitesi | en_US |
| dc.department-temp | [Erdem] Mehmet, Department of Industrial Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Koç] Çaĝrı, Department of Business Administration, Social Sciences University of Ankara, Altindag, Ankara, Turkey; [Yücel] Eda, Department of Industrial Engineering, TOBB University of Economics and Technology, Ankara, Turkey | en_US |
| dc.description.abstract | This paper introduces the electric home health care routing and scheduling problem with time windows and fast chargers. The problem aims to construct the daily routes of health care nurses so as to provide a series of services to the patients located at a scattered area. The problem minimizes the total cost, which comprises of total traveling cost of electric vehicles, total cost of uncovered jobs, and total costs of recharged energy. We develop an adaptive large neighborhood search heuristic, which contains a number of advanced efficient procedures tailored to handle specific features of the problem. The paper conducts extensive computational experiments on generated benchmark instances and assesses the competitiveness of the heuristic. Results show that the heuristic is highly effective on the problem. Our analyses quantify the advantages of considering all charger technologies, i.e., normal, fast- and super-fast. We show that the downgrading of competence levels of jobs yields an improvement in total cost. © 2022 Elsevier Ltd | en_US |
| dc.identifier.doi | 10.1016/j.cie.2022.108580 | |
| dc.identifier.issn | 0360-8352 | |
| dc.identifier.scopus | 2-s2.0-85136689202 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.uri | https://doi.org/10.1016/j.cie.2022.108580 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12712/36777 | |
| dc.identifier.volume | 172 | en_US |
| dc.identifier.wosquality | Q1 | |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier Ltd | en_US |
| dc.relation.ispartof | Computers & Industrial Engineering | en_US |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Adaptive Large Neighborhood Search | en_US |
| dc.subject | Electric Vehicles | en_US |
| dc.subject | Home Health Care Services | en_US |
| dc.subject | Vehicle Routing | en_US |
| dc.title | The Electric Home Health Care Routing and Scheduling Problem with Time Windows and Fast Chargers | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication |
