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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Benders decomposition in optimization
 Minaříková, Michaela ; Branda, Martin (advisor) ; Rusý, Tomáš (referee)
The Bachelor thesis is dealing with Benders decomposition in optimization, especially in stochastic linear programming. In the begining the reader will be introduced to the important terms used in the decomposition algorithm. Con- sequently it is demonstrated how to reformulate the problem of stochastic linear programming to a special structure suitable for Benders decomposition. In the third chapter, the decomposition algorithm, using the feasibility and optimality cuts, is explained including conditions of convergence of the algorithm. There follows modification of algorithm for two stage stochastic linear programming. Finally, we illustrate Benders algorithm on two smaller problems. 1
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Selected methods for solving integer programming problems
 Picková, Veronika ; Sekničková, Jana (advisor) ; Charvát, Karel (referee)
This final thesis work is dealing with the problems of mixed integer linear programming and their possible methods of solving. The reader will be introduced to the issues of integer programming in the first part of the work. There follow the different methods of solving in the second part, concretely the possibility of solving without the integer constraints and rounding the solution, the branch and bound method and the Gomory's method. The purpose of this work is to inform the reader about the Benders decomposing algorithm. Decomposing methods divide the original problem into two parts: a part with the constraints of integrity and a part without them. All of the explained methods are supported by illustrative examples. The third part of this thesis is the application of used methods to a concrete problem.
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