Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8933
Title: The Electric Home Health Care Routing and Scheduling Problem With Time Windows and Fast Chargers
Authors: Erdem, Mehmet
Koc, Cagri
Yucel, Eda
Keywords: Vehicle Routing
Home Health Care Services
Electric Vehicles
Adaptive Large Neighborhood Search
Publisher: Pergamon-Elsevier Science Ltd
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.
Description: Koc, Cagri/0000-0002-7377-204X; Yucel, Eda/0000-0002-3448-1522
URI: https://doi.org/10.1016/j.cie.2022.108580
ISSN: 0360-8352
1879-0550
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record



CORE Recommender

SCOPUSTM   
Citations

12
checked on May 17, 2025

WEB OF SCIENCETM
Citations

12
checked on May 17, 2025

Page view(s)

152
checked on May 5, 2025

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.