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Optymalizacja procesu wysyłki cukru

100%
Pytlak R., Stecz W.
Gospodarka Materiałowa i Logistyka
|
2014
|
issue 2
21-30
EN
We consider the sugar dispatching process at a sugar mill. The main goal of our work was to check an efficiency of the logistics system in the mill, find and correct the bottlenecks. Some methods for logistics processes optimization are presented. We base on the heuristics and CLP techniques for solving the scheduling problems. Some additional remarks about possibility of using the optimization methods in scheduling and logistics optimizations are presented too.
2
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Modele dla potrzeb rozwiązywania zadań optymalizacji taryf

100%
Pytlak R., Stecz W.
Gospodarka Materiałowa i Logistyka
|
2014
|
issue 7
24-32
EN
We present the methods of telecommunication tariff optimization from a point of client’s view. A client which wants to minimize his monthly fees tries to choose a proper tariff model. In case of large companies these models are more complicated and the optimization models should be used. We describe a simple MIP models and their modifications solved with CLP solvers. All the examples were solved with ILOG and ECLiPSe MIP and CLP solvers.
3
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System wspomagania pracy służb sanitarnych

81%
Pytlak R., Zawadzki T., Suski D., Stecz W.
Gospodarka Materiałowa i Logistyka
|
2014
|
issue 11
19-28
EN
We describe the information system that has been built for the support sanitary teams. The system is aimed at supporting analytical work which must be carried out when there is a risk of epidemic outbreak. It is meant to provide tools for predicting the size of an epidemic on the basis of the actual data collected during its course. Since sanitary teams try to control the size of the epidemics such a tool must model also sanitary teams activities. As a result a model for the prediction can be quite complicated in terms of the number of equations it contains. Furthermore, since a model is based on several parameters there must be a tool for finding these parameters on the basis on the actual data corresponding to the epidemic evolution. The paper describes the proposition of such a system. It presents, in some details, the main components of the system. In particular, the environment for building complex models (containing not only the epidemic model but also activities of sanitary teams trying to inhibit the epidemic) is discussed. Then, the module for a model calibration is presented. The module is a part of server for solving optimal control problems and can be accessed via Internet. Finally, we show how optimal control problems can be constructed with the aim of the efficient epidemic management. Some optimal control problems related to that issue are discussed and numerical results of its solution are presented.
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