研究生: |
Monica Indriani Monica Indriani |
---|---|
論文名稱: |
考慮需求不確定性和可持續性的醫療藥品庫存路徑問題的隨機規劃 Stochastic Programming for the Medical Drug Inventory Routing Problem Considering Demand Uncertainty and Sustainability |
指導教授: |
喻奉天
Vincent F. Yu |
口試委員: |
郭伯勳
Po-Hsun Kuo 吳政鴻 Cheng-Hung Wu |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 工業管理系 Department of Industrial Management |
論文出版年: | 2020 |
畢業學年度: | 108 |
語文別: | 英文 |
論文頁數: | 82 |
中文關鍵詞: | 庫存路徑問題 、可持續發展 、拉丁超立方體 、隨機規劃 、醫療藥品分配 |
外文關鍵詞: | Inventory Routing Problem, Sustainability, Latin Hypercube, Stochastic Programming, medical drug distribution |
相關次數: | 點閱:537 下載:0 |
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Medical drug shortages can have significant effects not only on patient
health but also on a government. Demand uncertainty, distribution, and inventory
policy are regarded as the main factors causing such shortages, and to avoid them
medical institutes tend to order or store more medical drugs than they need,
resulting in medical wastes that need to be properly addressed in order to mitigate
any financial burden and impact on the environment.
The inventory routing problem (IRP) appears to be a good approach to
model and solve the problem. This study thus extends IRP to propose a multiobjective
two-stage model that considers demand uncertainty and environmental
issues concerning the distribution of medical drugs. The first objective focuses on
the basic costs of inventory and distribution. Since medical wastes affect the
environment and should be recycled, we also include the concept of reverse
logistics. The second objective minimizes vehicle emissions resulting from
distribution and recycling processes. To deal with uncertainty, we apply two
different approaches based on the demand pattern probability to confirm the
robustness of the proposed model. To solve the model, the study employs the Latin
hypercube sequence to conducted the scenarios and develops a metaheuristic based
on the simulated annealing algorithm.
Finally, we report the results of numerical studies, including the
performance of the proposed models and the effect on the economy and
environment. The use of the Latin Hypercube and Annealing Simulation algorithm
is capable of solving the proposed model of IRP and can provide competitive results
compared to other algorithms. Furthermore, the model can show the resulting
emissions based on the process of distribution and waste management.
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