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Robust Organ Transportation via Cold Chain and Commercial Flight Networks | ||
| Advances in Industrial Engineering | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 26 اردیبهشت 1405 | ||
| شناسه دیجیتال (DOI): 10.22059/aie.2026.412182.1974 | ||
| نویسندگان | ||
| Mariam Sadat Shojaedin1؛ Parvaneh Samouei* 2 | ||
| 1Department of Industrial Engineering, Sharif University of Technology, International Campus, Kish Island, Iran. | ||
| 2Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran. | ||
| چکیده | ||
| Organ transplantation logistics demand rapid, reliable, and medically viable delivery solutions, especially when relying on commercial flight networks. The viability of an organ is severely constrained by its cold ischemia time—the duration an organ can remain functional outside the human body under refrigeration. This study formulates deterministic and robust mathematical models to optimize organ transport routing under uncertainty. The transportation network is modeled as a directed graph, where airports serve as nodes and scheduled flights as arcs, integrating constraints such as flight eligibility, connection handling time, and air traffic control prioritization. Building on a deterministic Resource-Constrained Shortest Path (RCSP) model, a model using Mulvey et al.'s robust optimization approach is extended. This allows the model to account for various real-world disruptions, including departure delays and scheduling inconsistencies, using multiple predefined scenarios. Furthermore, a penalty-based objective function is used to minimize arrival time and deviation across scenarios, ensuring stable and feasible routing decisions. The model is implemented via CPLEX, with experiments conducted on synthetic data for multiple organ types. Results demonstrate that the robust model, while more computationally intensive, yields significantly more resilient and feasible solutions across delay scenarios. Sensitivity analyses further highlight the critical roles of connection time and flight segment penalties. Overall, the proposed model offers a practical, scalable decision-support tool for transplant networks facing operational uncertainty. | ||
| کلیدواژهها | ||
| Organ transportation؛ robust optimization؛ cold ischemia time؛ commercial flight network | ||
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آمار تعداد مشاهده مقاله: 72 |
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