Distributed decision making model for demand and capacity sharing decisions in medical waste processing facilities
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Abstract (EN)
Medical wastes cause the infectious diseases and spread of them, chemical and physical damage, and thus pose a great danger to public and environmental health. The collection, transportation and disposal of these wastes are the responsibility of the municipalities, and the decision to send the waste to another facility in case of malfunctions and maintenance in the facilities that perform medical waste sterilization within the scope of the study is modeled with the Distributed Decision Making (DDM) method within a collaborative network structure. With the proposed DDM model, unlike the classical decision-making methods, it is aimed to meet the incoming demand with instant failure (stop) status, instant excess capacity and unmet amount of demand information for each of the members in a network model structure. In this way, wastes that need to be treated will be disposed of, and all of these wastes, which may lead to negative consequences, will be disposed of within the network structure in a way that provides less cost and various income alternatives. Capacity and demand sharing is optimized with the collaborative network structure model. According to the experimental results, there is an increase in the capacity utilization rate and the level of meeting the demand in the proposed network model, while there is a decrease in non-value-added efforts such as excess stock, lost sales cost and idleness of investment and workforce. In this study, a mathematical model has been proposed that provides a more effective and efficient use of the resources of country, together with the collaborative network structure between municipalities by looking at medical waste management from different perspectives.
Author
Ahmet Eray Bülter
How to Cite
Ahmet Eray Bülter (Master Thesis). Distributed decision making model for demand and capacity sharing decisions in medical waste processing facilities, 2021, Gazi University.
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