Literaturnachweis - Detailanzeige
Autor/inn/en | El Midaoui, Marouane; Qbadou, Mohammed; Mansour, Khalifa |
---|---|
Titel | Logistics Chain Optimization and Scheduling of Hospital Pharmacy Drugs Using Genetic Algorithms: Morocco Case |
Quelle | In: International Journal of Web-Based Learning and Teaching Technologies, 16 (2021) 2, S.54-64, Artikel 4 (11 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Zusatzinformation | ORCID (El Midaoui, Marouane) ORCID (Qbadou, Mohammed) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 1548-1093 |
Schlagwörter | Foreign Countries; Health Services; Hospitals; Pharmacy; Drug Therapy; Delivery Systems; Mathematics; Geographic Regions; Transportation; Simulation; Proximity; Morocco |
Abstract | In recent years, the health sector has faced increasingly important challenges. Due to the economic crisis and competitions, hospitals are facing many issues affecting the supply chain, such as budget cuts or lack thereof as well as insufficient human resources. Although essential for an excellent service, logistics take up a considerable part of the budget as challenges need to be addressed such as delays in drugs delivery, transportation and storage conditions, routing and scheduling. As to governance, each hospital is assigned to a specific region, which cannot be defined due to political, demographic, or geographic issues. This paper focuses on multi-depot vehicle routing problem (MDVRP) in healthcare logistics to feed the hospital pharmacies. The idea is to apply MDVRP's approach to the health sector, specifically hospital pharmacies. In this projection, hospitals are considered to present clients, and central pharmacies present deposits. This problem (the MDVRP) is known by this nature NP-hard. For that, the heuristic method was used as genetic algorithm to solve the problem. The paper is organized as follows, the first section discusses, compares, and proposes clustering methods for healthcare facilities with applying them on Moroccan hospitals case; the second section proposes a genetic algorithm to resolve the MDVRP with a simulation. (As Provided). |
Anmerkungen | IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: journals@igi-global.com; Web site: https://www.igi-global.com/journals/ |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |