In regression models normally, both of data and parameters are considered as crisp. But, in some cases, for improving the prediction, we need to prepare and use a regression model with imprecise coefficients. In this case the normal regression models are not suitable, so fuzzy regression can be fair replacement models. In this paper we consider the least square and least absolute deviation familiar methods to compare the mention models. Finally we apply these approaches to geography data (TMP, PRC, Latitude and Longitude) with symmetric fuzzy observations.
In this paper, we consider the bilevel linear programming problem (BLPP)
where all the coefficients in the problem are interval type-2 triangular
fuzzy numbers (IT2TFNs). First, we convert a BLPP with IT2TFN parameters to
an interval BLPP. In the next step, we solve BLPPs and obtain optimal
solution as an IT2TFN.
Background: The cost of health care is a large part of every household’s budget. On the other hand, as an economic entity, the hospital is constantly faced with different aspects of cost and revenue. So, we are dealing with conflicting objectives. Objectives: The main purpose of the research is to help financial management in a specialty hospital. This article provides part of operational research under bi-level optimization for hospital managers to provide targeted financial planning. The method is based on the fact that the objective is to maximize the hospital income on one level, and on the other level, the objective is to reduce the patient’s payment. Methods: The hierarchical and decentralized optimization problem is written as a bi-level model that minimizes patient costs and maximizes hospital revenues, which is an NP-Hard problem. The optimal solution to this problem is obtained using a genetic algorithm. Then, the hospital’s performance is evaluated by the Pabon Lasso diagram. It is shown that the use of this model has a significant effect on the hospital’s performance. Results: Implementation of this model in the studied hospital shows that patient payment costs decreased and hospital income increased (reaching equilibrium point). Conclusion: Hospital performance after model implementation was evaluated by the Pabon Lasso diagram and showed that it has an effective role in hospital performance.
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