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National Repository of Grey Literature 1 records found  Search took 0.01 seconds. 
Exact penalization in optimization
 Šešulka, Marek ; Branda, Martin (advisor) ; Kopa, Miloš (referee)
This thesis deals with one of the possible different approaches to solving nonlinear optimization problems by convertion to finding non-bounded extrema of function, where constrains are transfered to objective function via penalty function. We will introduce exterior penalty function method and appropriate algorithm for solving this type for problems. The thesis also deals with exact penalty functions, which do not requires limit approximation of the penalty pa- rameter to infinity. Then we deal with integer binary nonlinear progamming, where several suitable penalty functions are presented to solve this type of pro- blem. In the numerical part, the thesis deals with the minimization of risk at the specifed minimum expected return on the sparse portfolio. We observe the effect of changing the penalty parameter on the results of ten different minimization problems calculating risk of sparsity portfolios. 1
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