Logistics Chain Optimization and Scheduling of Hospital Pharmacy Drugs Using Genetic Algorithms: Morocco Case

Logistics Chain Optimization and Scheduling of Hospital Pharmacy Drugs Using Genetic Algorithms: Morocco Case

Marouane El Midaoui, Mohammed Qbadou, Khalifa Mansouri
DOI: 10.4018/IJWLTT.2021030104
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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.
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3. Regional Clustering Based On Performance Indicators

Many approaches have proposed to cluster hospitals (Thomas, 1979; Thomas et al., 1981). In our work, we propose clustering by Performance indicators linked to regions instead of hospitals, because the creation of centralized pharmacies is for the purpose of serving a hospital pharmacy in determined regions and also the data is grouped by regions, the Performance indicators in our case are Hospital Bed Capacity (HBC) by region (Table 1).

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