The electric home health care routing and scheduling problem with time windows and fast chargers. (October 2022)

• Record Type: Journal Article
• Authors: Erdem, Mehmet; Koç, Çağrı; Yücel, Eda
• Is Part Of: Computers & industrial engineering. Volume 172:Part A(2022)
• Publication Date: 2022-10
• Subjects: Vehicle routing -- Home health care services -- Electric vehicles -- Adaptive large neighborhood search; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108580
• Languages: English
• ISSNs: 0360-8352

Abstract

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. Highlights: We introduce a variant of the home health care routing problem. We explore the use of electric vehicles and multiple charging technologies. We develop an adaptive large neighborhood search heuristic. We perform extensive analyses to provide several managerial and policy insights. We quantify the benefits of considering three charging technologies.