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To coordinate the supply chain risk caused by demand uncertainty, this paper proposed a flexible return strategy under demand uncertainty, in which the retailer can choose return quantity independently by put option after the selling season, while the return quantity is usually determined by the supplier in the classical return strategy. In our novel return strategy, the exercise price is not fixed, and we developed the base model of this strategy, named the selective buyback contracts model. We have solved the optimal pricing and ordering strategies of supply chain members. Numerical studies demonstrated that the contracts can coordinate a supply chain with one retailer and one supplier, and the supplier can adjust the profit distribution of the supply chain by adjusting the option exercise price. Compared with other return strategies, the selective buyback contracts give the retailer more power of choice, and the supplier receives risk compensation from the put options.
Pan Guo; Yanlin Jia; Junwei Gan; Xiaofeng Li. Optimal Pricing and Ordering Strategies with a Flexible Return Strategy under Uncertainty. Mathematics 2021, 9, 2097 .
AMA StylePan Guo, Yanlin Jia, Junwei Gan, Xiaofeng Li. Optimal Pricing and Ordering Strategies with a Flexible Return Strategy under Uncertainty. Mathematics. 2021; 9 (17):2097.
Chicago/Turabian StylePan Guo; Yanlin Jia; Junwei Gan; Xiaofeng Li. 2021. "Optimal Pricing and Ordering Strategies with a Flexible Return Strategy under Uncertainty." Mathematics 9, no. 17: 2097.
In China, emergency room residents (EMRs) generally face high working intensity. It is particularly important to arrange the working shifts of EMRs in a scientific way to balance their work and rest time. However, in existing studies, most of the scheduling models are based on the individual doctor or nurse as a unit, less considering the actuality of operation and management of emergency department (ED) in large public hospitals in China. Besides, the depiction of the hard and soft constraints of EMR scheduling in China is insufficient. So in order to obtain the scientific and reasonable scheduling shifts, this paper considers various management rules in a hospital, physicians’ personal preferences, and the time requirements of their personal learning and living and takes the minimum deviation variables from the soft constraints as the objective function to construct a mixed integer programming model with the doctor group as the scheduling unit. The analytic hierarchy process (AHP) is used to determine the weights of deviation variables. Then, IBM ILOG CPLEX 12.8 is used to solve the model. The feasibility and effectiveness of the scheduling method are verified by the actual case from West China Hospital of Sichuan University. The scheduling results can meet the EMRs’ flexible work plans and the preferences of the doctor teams for the shifts and rest days. Compared with the current manual scheduling, the proposed method can greatly improve the efficiency and rationality of shift scheduling. In addition, the proposed scheduling method also provides a reference for EMR scheduling in other China’s high-grade large public hospitals.
Mingying Tan; Junwei Gan; Qunrong Ren. Scheduling Emergency Physicians Based on a Multiobjective Programming Approach: A Case Study of West China Hospital of Sichuan University. Journal of Healthcare Engineering 2019, 2019, 1 -9.
AMA StyleMingying Tan, Junwei Gan, Qunrong Ren. Scheduling Emergency Physicians Based on a Multiobjective Programming Approach: A Case Study of West China Hospital of Sichuan University. Journal of Healthcare Engineering. 2019; 2019 ():1-9.
Chicago/Turabian StyleMingying Tan; Junwei Gan; Qunrong Ren. 2019. "Scheduling Emergency Physicians Based on a Multiobjective Programming Approach: A Case Study of West China Hospital of Sichuan University." Journal of Healthcare Engineering 2019, no. : 1-9.
At present, the recycling rate of End-of-life vehicles (ELVs) in China is far lower than the heavily motorized countries, resulting in severe environmental pollution, waste of resource and hidden traffic troubles, which has a negative impact on China’s economic and social sustainable development. With the arrival of the peak season of generating ELVs in China, it is urgent and important to improve the recycling rate of ELVs. The recycling rate of ELVs is influenced by multiple factors together. The existing research about the identification of influence factors of ELV recycling rate fewer considers the interaction effect among different factors. To fill the gap, firstly the influence factors are analyzed from standpoints of economy, policy, recycling network and others. Then a hybrid model based on DEMATEL (decision making trial and evaluation laboratory) and intuitionistic fuzzy sets is employed to examine the cause–effect relationships among factors. In the study, the vagueness of decision makers’ judgment and linguistic inaccuracy is dealt with effectively by intuitionistic fuzzy sets. The research results reveal “fiscal subsidy”, “government’s restrictive policies to reuse ELVs parts”, “coordination of the industry agencies”, “participation of automobile manufacturer” and “supervision of the government” are most significant criteria influencing the recycling rate of ELVs in China. A sensitivity analysis is conducted to verify the robustness of results. Lastly, according to the critical influencing factors identified, some pertinent suggestions to the government, ELV recycling enterprise, owner and vehicle manufacturer are put forward. In addition, the future research directions are proposed.
Junwei Gan; Li Luo. Using DEMATEL and Intuitionistic Fuzzy Sets to Identify Critical Factors Influencing the Recycling Rate of End-Of-Life Vehicles in China. Sustainability 2017, 9, 1873 .
AMA StyleJunwei Gan, Li Luo. Using DEMATEL and Intuitionistic Fuzzy Sets to Identify Critical Factors Influencing the Recycling Rate of End-Of-Life Vehicles in China. Sustainability. 2017; 9 (10):1873.
Chicago/Turabian StyleJunwei Gan; Li Luo. 2017. "Using DEMATEL and Intuitionistic Fuzzy Sets to Identify Critical Factors Influencing the Recycling Rate of End-Of-Life Vehicles in China." Sustainability 9, no. 10: 1873.