C61 - Optimization Techniques; Programming Models; Dynamic AnalysisReturn

In developed countries, day surgery has been used as a significant tool of efficiency increase in the health care system over the last few decades. However, its development is not sufficient in the Slovak conditions in spite of the support of the Ministry of Health of the Slovak Republic. Its use in the unstable conditions of the Slovak health system represents the main reason. The paper presents a partial output of the research that focuses on day surgery development in order to increase an efficiency of the health system in Slovakia. Its primary aim is to highlight a significance of Malmquist indices' application in evaluation of day surgery processes of adult patients. The outputs represent a valuable platform for health and social policies' creators.

This paper analyses the monetary policy of a central bank in a simple deterministic and continuous dynamic non-linear New-Keynesian model with an active central bank conducting monetary policy within inflation targeting framework. To meet this purpose, first we derive two differential equations capturing the dynamics in the economy: the dynamic IS curve representing the commodity market and the Phillips curve capturing the connection between the real and nominal sectors of the economy in a continuous form. By introducing a quadratic loss function commonly used in New Keynesian Economics we get optimal control problem which solution will be analysed with the use of fuzzy control. Then we introduce a modified form of the Taylor rule and analyse the solution of the same differential equations capturing the dynamics of the economy using Taylor rule instead of loss function. The comparison of the solutions of both models will be demonstrated in examples in which the main characteristic of dynamics of production and inflation are displayed.

In the presented paper we develop model of apportionment of cost generated by variability and mean value of flows from (to) shared services centre. It can be either cash pool or distribution centre, or even some kind of customer service centre. The apportionment formula for the cost of capacity generated by flow variability turns out to be regression coefficient of flow to (from) the distribution centre (cash pool) generated by particular company within the multibusiness enterprise as endogenous variable to flow of inventory (cash) for the whole distribution centre (cash pool) as exogenous variable. The cost generated by the flow of requirements (goods, money) itself, i.e. by the mean value of the flow, has to be split between SSC customers according to their share on that flow. Result does not depend on the form of cost function as long as it is strictly increasing function of flow from (into) SSC (orders, stock, cash) and of mean of that flow.