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Risk Management in Projects by Bayesian Belief Networks
, M.Sc. Thesis Sharif University of Technology ; Haji, Alireza (Supervisor)
Abstract
Risk management is one of the important phases of a project life cycle. There are several quantitative and qualitative methods to determine and plan the proper reaction risks in a project. These methods aim to prevent additional and unnecessary costs. Project managers, stake holders and beneficiaries always believe that risk management of project engineering as one of the importance parts. Although there are multiple methods that can evaluate risk, but there is still research problems especially for risk qualitative and quantitative prediction. This gets more serious after evaluating and minimizing risks effects considering the other risks’ damaging effects which have not been considered. In...
Study of End-to-End Voting Systems Helios and Scantegrity II
, M.Sc. Thesis Sharif University of Technology ; Khazaei, Shahram (Supervisor)
Abstract
Voting is a detachable part of the democratic governments. In the era of modern computer systems, the need for electronic voting systems in no longer avoidable.Designing a secure electronic voting system is a difficult problem since both privacy and integrity must be achieved at the same time. This difficulty has cast the problem to the center of attention of many researchers.In this thesis we will consider the new generation of voting systems known as end-to-end that were designed to solve the problems in the previous generations of voting systems and to uphold the security of the system. Many of end-toend voting systems use concepts of cryptography in addition to machine tools.A central...
An Augmented Weighted Tchebycheff Approach for Solving a Multi-Objective Model for Supplier Selection and Oorder Allocation under Volume Discount
(Case study: Supplier selection and order allocation in a drilling company)
,
M.Sc. Thesis
Sharif University of Technology
;
Mahdavi-Amiri, Nezam
(Supervisor)
Abstract
In order to achieve a compromised solution for a multi-objective problem, we make use of the Tchebycheff norm to minimize the distance from the current estimate of the objectives from the ideal point. Solutions obtained from the Tchebycheff approach are weakly efficient for multi-objective problems. For a better solution, the augmented weighted Tchebycheff norm has been proposed. Here, we use the satisficing tradeoff algorithm to solve the augmented weighted Tchebycheff problems. Since the supplier selection problem is usually a multi objective problem, we use the augmented weighted Tchebycheff method for obtaining its solutions. Numerical results are presented illustrating the performance...