期刊
RISK ANALYSIS
卷 40, 期 9, 页码 1863-1886出版社
WILEY
DOI: 10.1111/risa.13509
关键词
Bilevel equilibrium model; location-allocation problem; medical waste; risk management
类别
资金
- National Natural Science Foundation of China [71971150, 71501137, 71771157, 71301109]
- Sichuan Science and Technology Program [2019JDR0167]
- Sichuan Social Science Planning Fund Office [SC18TJ014]
- General Program of China Postdoctoral Science Foundation [2015M572480, 2017M610609]
- International Postdoctoral Exchange Fellowship Program of China Postdoctoral Council [20150028]
- project of Research Center for System Sciences and Enterprise Development [Xq16B05]
- Fundamental Research Funds for the Central Universities of China
- Sichuan University [2019hhs-16, skqy201647, 20826041C4201, SXYPY202004]
The risk of medical waste pollution and huge demand of daily medical waste disposal pose great difficulties to medical waste management. Establishing medical waste disposal centers (MWDCs) is considered one of the ways to reduce the environmental and public risk of medical waste pollution. However, how to serve the medical waste disposal demand in optimal MWDCs' locations is a key challenge due to the complexity of the whole system and relationships among stakeholders. This article develops a soft-path solution for reducing risks as well as mitigating the related costs by optimizing the MWDC location-allocation problem. A risk mitigation-oriented bilevel equilibrium optimization model is developed for modeling the Stackelberg game behavior between the local government and the medical institutions. The objectives of the local government are minimizing the total risk of loss, the subsidy costs, and the investment cost of building the MWDCs, while minimizing the disposal and transportation costs are the objectives at the medical institution level. Fuzzy random variables are introduced by combining insufficient historical data with expert knowledge via consulting surveys to describe the coexisting uncertainties in the data. To solve the model, a hybrid approach combined with the interactive fuzzy programming technique and an Entropy-Boltzmann selection-based genetic algorithm are designed and tested. The Chengdu Medical Waste Disposal Centers Planning Project is used as a practical application. The results show that it is possible to achieve a balanced market with higher economic efficiency and significantly reduced risk through an appropriate principle of interactive actions between the bilevel stakeholders.
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