|
|
Stochastic Programming Algorithms
Klimeš, Lubomír ; Mrázková, Eva (oponent) ; Popela, Pavel (vedoucí práce)
Stochastic programming and optimization are powerful tools for solving a wide variety of engineering problems including uncertainty. The progressive hedging algorithm is an effective decomposition method for solving scenario-based stochastic programmes. Due to the vertical decomposition, this algorithm can be implemented in parallel thereby the computing time and other resources could be considerably spared. The theoretical part of this master's thesis deals with mathematical and especially with stochastic programming. Further, the progressive hedging algorithm is presented and discussed in detail. In the practical part, the original parallel implementation of the progressive hedging algorithm is suggested, fruitfully discussed and tested to simple problems. Furthermore, the presented parallel implementation is used for solving the continuous casting process of steel slabs and the results are appraised.
|
|
|
Stochastic optimization in AIMMS
Kůdela, Jakub ; Mrázková, Eva (oponent) ; Popela, Pavel (vedoucí práce)
This master’s thesis introduces the basic concepts of mathematical and, most importantly, stochastic programming. Moreover, it gives a description of the usage of the software AIMMS in constructing and solving various optimization problems. Our main goal is to program several methods for solving these stochastic programming problems in AIMMS and show the usage and usefulness of these methods on chosen problems. One of the problems we chose is an incineration plant model. All the AIMMS programs, that we describe and use in our text, and their source codes will be enclosed in the appendices.
|
|
|
Stochastic optimization in AIMMS
Kůdela, Jakub ; Mrázková, Eva (oponent) ; Popela, Pavel (vedoucí práce)
This master’s thesis introduces the basic concepts of mathematical and, most importantly, stochastic programming. Moreover, it gives a description of the usage of the software AIMMS in constructing and solving various optimization problems. Our main goal is to program several methods for solving these stochastic programming problems in AIMMS and show the usage and usefulness of these methods on chosen problems. One of the problems we chose is an incineration plant model. All the AIMMS programs, that we describe and use in our text, and their source codes will be enclosed in the appendices.
|
|
|
Stochastic Programming Algorithms
Klimeš, Lubomír ; Mrázková, Eva (oponent) ; Popela, Pavel (vedoucí práce)
Stochastic programming and optimization are powerful tools for solving a wide variety of engineering problems including uncertainty. The progressive hedging algorithm is an effective decomposition method for solving scenario-based stochastic programmes. Due to the vertical decomposition, this algorithm can be implemented in parallel thereby the computing time and other resources could be considerably spared. The theoretical part of this master's thesis deals with mathematical and especially with stochastic programming. Further, the progressive hedging algorithm is presented and discussed in detail. In the practical part, the original parallel implementation of the progressive hedging algorithm is suggested, fruitfully discussed and tested to simple problems. Furthermore, the presented parallel implementation is used for solving the continuous casting process of steel slabs and the results are appraised.
|
host ::
RSS.