This paper discusses the principle of applying the reasoning method of the smallest set covering model which is suitable to diagnosis expert system to the classification model.

According to the characteristic of urban disaster prevention and mitigation facilities location problem, a two-stages process of hierarchical location is presented as follows:(1) location set covering model is used to determine the necessary minimum numbers of facilities and its locations, that can cover all demanded points and be taken as the basic-level facilities;

Designing a simulative model for the forecast and optimal placement of casualty evacuation assets based on the probabilistic location set covering problem

In order to find optimization method for location of municipal solid waste (MSW) transfer stations, according to the characteristics of MSW collection and transportation system, the idea of reverse logistics system for location planning was introduced in this study. Location of MSW transfer stations were primarily optimized by setting covering model, and then the alternative MSW transfer stations were established.

A new 0/1 programming model, which is a generalization of the set covering model, is then presented and applied to a hypothetical reserve selection problem.

We then formulate a Location Set Covering model with a variable (optimal) number of servers per service center (or facility).

The Ex-Post Evaluation of the Minimum Local Reliability Level: An Enhanced Probabilistic Location Set Covering Model

A novel application of the set covering model to the analysis of cytological samples is then discussed.

A hierarchical objective set covering model for emergency medical service vehicle deployment.

This paper discusses the principle of applying the reasoning method of the smallest set covering model which is suitable to diagnosis expert system to the classification model. In this method, data are produced by production rules of the classification model. The degree of certainty is calculated by the approximation of two phenomenon subsets, with the computing formula and the reasoning route presented.

In this paper the hierarchical location problem of urban disaster prevention and mitigation facilities is put forward and classified. This hierarchical location problem is modelled in both types, in which higher-lower level facilities are relatively independent and mutual subordinate respectively. According to the characteristic of urban disaster prevention and mitigation facilities location problem, a two-stages process of hierarchical location is presented as follows:(1) location set covering model is used...

In this paper the hierarchical location problem of urban disaster prevention and mitigation facilities is put forward and classified. This hierarchical location problem is modelled in both types, in which higher-lower level facilities are relatively independent and mutual subordinate respectively. According to the characteristic of urban disaster prevention and mitigation facilities location problem, a two-stages process of hierarchical location is presented as follows:(1) location set covering model is used to determine the necessary minimum numbers of facilities and its locations, that can cover all demanded points and be taken as the basic-level facilities; (2) for the independent type of hierarchical location problem, the maximal covering criterion is used to determine the locations of high-level facilities, for the subordinate type of hierarchical location problem, the minimum sum criterion is used to determine the locations of high-level facilities. The application of the model of hierarchical location problem is also discussed.

Objective:To design a simulative model for the forecast and optimal placement of mass casualty evacuation assets.Methods: An operation research module named the location selection problem was introduced in this study.The probabilistic location set covering problem was chosen as the theoretical model for optimal placement of mass casualty evacuation assets.Several indeterminate factors were analyzed in details,including the availability;capacity and velocity and effective work time of evacuation assets.The ideal...

Objective:To design a simulative model for the forecast and optimal placement of mass casualty evacuation assets.Methods: An operation research module named the location selection problem was introduced in this study.The probabilistic location set covering problem was chosen as the theoretical model for optimal placement of mass casualty evacuation assets.Several indeterminate factors were analyzed in details,including the availability;capacity and velocity and effective work time of evacuation assets.The ideal statistical distributions were determined by the characteristics of these variables.Results: According to the principle of Monte Carlo simulation and based on the probabilistic location set covering problem,random numbers fitting theoretical probabilistic distributions were generated to simulate those indeterminate factors,based on which a simulative model for optimal placement of casualty evacuation assets was designed.Conclusion: This simulative model may be used as a basis for further development of a computer-assisted program and as a reference for medical administration commanders at different levels.