The scheduling problem in surgery is difficult because, in addition of the planning of the operating rooms which are the most expensive resources in hospitals, each surgery requires a combination of human and material...The scheduling problem in surgery is difficult because, in addition of the planning of the operating rooms which are the most expensive resources in hospitals, each surgery requires a combination of human and material resources. In this paper, the authors address a surgery scheduling problem which arises in operated health care facility. Moreover, the authors consider simultaneously materiel and human resources. This problem is a three-stages flow shop scheduling environment. The first stage(ward) contains a limited number of resources of the same type(beds);The second stage contains different resources with limited capacity(operating rooms, surgeons, nurses, anesthesiologists)and the third stage contains a limited number of recovery beds. There is also a limited number of transporters(porters) between the ward and the other stages. The objective of the problem is to minimize the completion time of the last patient(makespan). The authors formulate this NP-Hard problem in a mixed integer programming model and conduct computational experiments to evaluate the performance of the proposed model.展开更多
Credit scoring is one of the key problems in financial risk managements.This paper studies the credit scoring problem based on the set-valued identification method,which is used to explain the relation between the ind...Credit scoring is one of the key problems in financial risk managements.This paper studies the credit scoring problem based on the set-valued identification method,which is used to explain the relation between the individual attribute vectors and classification for the credit worthy and credit worthless lenders.In particular,system parameters are estimated by the set-valued identification algorithm based on a given recognition criteria.In order to illustrate the efficiency of the proposed method,practical experiments are conducted for credit card applicants of Australia and credit card holders from Taiwan,respectively.The empirical results show that the set-valued model has a higher prediction accuracy on both small and large numbers of data set compared with logistic regression model.Furthermore,parameters estimated by the set-valued identification method are more stable,which provide a meaningful and logical explanation for extracting factors that influence the borrowers’credit scorings.展开更多
文摘The scheduling problem in surgery is difficult because, in addition of the planning of the operating rooms which are the most expensive resources in hospitals, each surgery requires a combination of human and material resources. In this paper, the authors address a surgery scheduling problem which arises in operated health care facility. Moreover, the authors consider simultaneously materiel and human resources. This problem is a three-stages flow shop scheduling environment. The first stage(ward) contains a limited number of resources of the same type(beds);The second stage contains different resources with limited capacity(operating rooms, surgeons, nurses, anesthesiologists)and the third stage contains a limited number of recovery beds. There is also a limited number of transporters(porters) between the ward and the other stages. The objective of the problem is to minimize the completion time of the last patient(makespan). The authors formulate this NP-Hard problem in a mixed integer programming model and conduct computational experiments to evaluate the performance of the proposed model.
基金supported by the National Key R&D Program of China under Grant No.2018YFA0703800the National Natural Science Foundation of China under Grant No.61622309the Verg Foundation(Sweden)。
文摘Credit scoring is one of the key problems in financial risk managements.This paper studies the credit scoring problem based on the set-valued identification method,which is used to explain the relation between the individual attribute vectors and classification for the credit worthy and credit worthless lenders.In particular,system parameters are estimated by the set-valued identification algorithm based on a given recognition criteria.In order to illustrate the efficiency of the proposed method,practical experiments are conducted for credit card applicants of Australia and credit card holders from Taiwan,respectively.The empirical results show that the set-valued model has a higher prediction accuracy on both small and large numbers of data set compared with logistic regression model.Furthermore,parameters estimated by the set-valued identification method are more stable,which provide a meaningful and logical explanation for extracting factors that influence the borrowers’credit scorings.