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Solving MDVRP Using Two-Step Clustering: A Case Study of Pharmaceutical Distribution in Tehran | ||
| Advances in Industrial Engineering | ||
| دوره 58، شماره 1، شهریور 2024، صفحه 85-102 اصل مقاله (903.57 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/aie.2024.363992.1879 | ||
| نویسندگان | ||
| Abolfazl Bagheri Tofighi1؛ Faezeh Gorji2؛ Alireza Deravi1؛ Erfan HassanNayebi* 3 | ||
| 1Department of Industrial Engineering & Management Systems, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Ave., Tehran, Iran | ||
| 2Department of Industrial Engineering & Management Systems, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Ave., Tehran, Iran | ||
| 3Industrial Engineering Department, Sharif University of Technology, 11155-1639 Tehran, Iran | ||
| چکیده | ||
| The healthcare sector has recently encountered significant challenges, including limited funding and intense competition. These issues have adversely impacted hospital supply chains, resulting in budget cuts, staffing shortages, and logistical difficulties. This study introduces a novel two-step clustering approach to address the multi-depot vehicle routing problem (MDVRP) in healthcare logistics, specifically focusing on optimizing the delivery of pharmaceutical supplies to hospital pharmacies in Tehran. The method begins with the K-means algorithm to identify optimal distribution centers in the first step. In the second step, K-means clustering, incorporating vehicle capacity and demand values, is applied to each distribution center to allocate demand points for each vehicle. The vehicle routes are then determined by solving the traveling salesman problem. By optimizing the number of distribution centers using the silhouette score, which resulted in a score of 0.3567 for four centers, the study shows that deploying five vehicles from four strategically located centers can meet the needs of Tehran hospitals with a total travel distance of 119.68 km. A comparative analysis with two alternative methods reveals that the proposed approach offers a 14% improvement in minimizing the total travel distance. This method not only helps identify optimal locations for new distribution centers but also develops efficient routing plans for pharmaceutical distribution, ultimately reducing costs and improving service quality within healthcare logistics. | ||
| کلیدواژهها | ||
| Drugs Delivery؛ Two-Step Clustering؛ Hospital Logistics؛ MDVRP؛ K-Means | ||
| مراجع | ||
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