Stohastiskā pieeja projekta izpildes laika un izmaksu novērtēšanai
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Latvijas Universitāte
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lav
Abstract
Bakalaura darbs veltīts diviem projekta vadības uzdevumiem, kas skatīti pie nosacījuma, ka aktivitāšu parametri uzdoti kā gadījuma lielumi. Projekta izpildes laika novērtēšanai salīdzinātas stohastiskās programmēšanas, PERT, Skulli-Šuma, un Montekarlo simulāciju metodes. Apskatīts arī projekta īstenošanas izmaksu un laika optimizācijas algoritms, kas balstās uz simulācijām un kvadrātisko programmēšanu. Visas metodes ilustrētas ar skaitliskiem piemēriem, darbam pievienoti programmēšanas valodā R izveidotie kodi, kā arī programmās TORA un Matlab veiktie aprēķini.
In the bachelor’s thesis, two project management tasks are studied on the condition that the activity parameters are set as random variables. For the project execution time estimation stochastic programming, PERT, Sculli-Shum, and Monte Carlo simulation methods are compared. The project implementation cost and time optimization algorithm based on simulations and quadratic programming is also considered. All the methods are illustrated with numerical examples, additionally, enclosed in the thesis is the source code written in the programming language R, as well as the calculations done in the programs TORA and Matlab.
In the bachelor’s thesis, two project management tasks are studied on the condition that the activity parameters are set as random variables. For the project execution time estimation stochastic programming, PERT, Sculli-Shum, and Monte Carlo simulation methods are compared. The project implementation cost and time optimization algorithm based on simulations and quadratic programming is also considered. All the methods are illustrated with numerical examples, additionally, enclosed in the thesis is the source code written in the programming language R, as well as the calculations done in the programs TORA and Matlab.