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    A Novel Framework for Change Management Leadership with Focus on Human Resource (HR) Factors

    , M.Sc. Thesis Sharif University of Technology Javan Bakht, Mohammad (Author) ;
    The world around us changes almost every second, so the economy in this world feels it more by every single minute. When we look at the organizational structures, they experience lots of things for keeping the companies competitive and the human resources have the main role among the other stimulating factors.The human resource management and its improvements have done a lot in this century to organize and manage the human problems in organizations. After that those companies that had more effective strategies become on top of this important management system. By changing fast the work models companies experience more and immediate changes that may not happen even through the years. In this... 

    A Markov Decision Processes Model for Supplier Selection in Supply-Chain Management Under Uncertainty

    , M.Sc. Thesis Sharif University of Technology Milani, Hamed (Author) ; Haji, Alireza (Supervisor)
    There are several types of uncertainty in supply chains that cause some difficulties in the planning of a supply chain. Uncertainty on the supply side can cause interruptions in the quality, quantity, or delivery time of orders. To avoid such interruptions, retailers usually contract with two different suppliers for a common good. In this setting, one of the suppliers has higher reliability and higher price, while the other supplier offers a lower price but has a lower level of reliability. In other words, to ensure a lower level of uncertainty, retailers have to pay more. This is one of the main tradeoffs in the dual sourcing strategy. In this thesis, we consider a two-echelon supply chain... 

    An Evolutionary Decision Model for Solving Road Maintenance Problems

    , M.Sc. Thesis Sharif University of Technology Khalifeh, Vahid (Author) ; Pourzahedi, Hossein (Supervisor)
    Pavement maintenance and rehabilitation is an important problem in road pavement programming. Pavements experience significant distress over its life due to passage of vehicle (particularly heavy trucks), as well as abrupt variation in temperature (freeze and thaw). This would deteriorate pavements and reduces their serviceability. Rise of pavement maintenance costs places higher importance upon the need for maintenance programming. This study employs an evolutionary model to optimize the long-run benefit of the maintenance program. The model is stochastic in nature, and imbeds a Markovian decision procedure in the model to take into account such variabilities. The model is applied on... 

    A Model to Predict the Railway Track Deterioration and Provide a Decision-Support System for Maintenance by Life Cycle Cost

    , M.Sc. Thesis Sharif University of Technology Hashemian, Elyas (Author) ; Shafahi, Yousef (Supervisor)
    Rail transport system plays an important role in the development of the economies of the countries. This system is worn out over time by operating and weather conditions and requires maintenance and repair. One of the objectives of maintenance operations is to maintain tracks in an acceptable level and prevent their excessive deviation from the optimal situation. This deviation is called geometric irregular deviation. If these irregularities go away, they can cause traffic accidents and derailment in addition to losing travel convenience. So avoiding the deviation of the tracks is a very important. Maintenance management systems in the past few decades have been considered by the experts in... 

    A Fuzzy Multi-Criteria Approach to Sustainable Development Case Study of Hendurabi Island in Iran

    , Ph.D. Dissertation Sharif University of Technology Mounesan, Ali Asghar (Author) ; Abrishamchi, Ahmad (Supervisor) ; Maknoon, Reza (Co-Supervisor)
    The main objective of this research is to provide a framework by which decision-makers can evaluate and compare alternatives for sustainable development planning under uncertain dynamic future considering the risk and uncertainty associated with human judgment as well as the uncertain future. This approach combines the Delphi method, fuzzy set theory, and a discrete multi-criteria method based on prospect theory (TODIM). TODIM (an acronym in Portuguese for iterative MCDM) method is a particular multi-criteria approach based on the prospect theory. A qualitative Delphi technique is used to identify a set of qualitative sustainability criteria and to rate the alternatives accordingly. The... 

    A Two Stage Approach based for Suppliers Selection and Order Allocation in Green Supply Chain

    , M.Sc. Thesis Sharif University of Technology Ramezanzadeh Baraki, Roohollah (Author) ; Kianfar, Farhad (Supervisor)
    In recent years, environmental issues has been gaining a great deal of attention in the field of Supply Chain and Supplier Selection. In this research, we first review the current literature and then we try to find the research gap in this area. According to the studies done in this area, no research on supplier selection and optimal order allocation to the suppliers have simultaneously investigated environmental issues, the possibility of storage, green routing of vehicles, purchasing discount, multi-product, and multi-period state in a green supply chain. Therefore, in this study, a multi-objective mathematical model is proposed for supplier selection and optimal order allocation in a... 

    A new Optimization Approach for Solving Well Placement Problem under Uncertainty Assessment

    , M.Sc. Thesis Sharif University of Technology Darabi, Hamed (Author) ; Massihi, Mohsen (Supervisor) ; Roosta Azad, Reza (Supervisor)
    Determining the best location for new wells is a complex problem that depends on reservoir and fluid properties, well and surface equipment specifications, and economic criteria. Various approaches have been proposed for this problem. Among those, direct optimization using the simulator as the evaluation function, although accurate, is in most cases infeasible due to the number of simulations required. This study proposes a hybrid optimization technique (HGA) based on the genetic algorithm (GA) with helper functions based on the polytope algorithm and the neural network. Hybridization of the GA with these helper methods introduces hill-climbing into the stochastic search and also makes use... 

    A Semisupervised Classification Algorithm for Data Streams Using Decision Tree Algorithm

    , M.Sc. Thesis Sharif University of Technology Gholipour Shahraki, Ameneh (Author) ; Beigy, Hamid (Supervisor)
    Nowadays, living in information era has forced us to face with a great deal of problems of which the input data is received like a nonstop endless stream. Intrusion detection in networks or filtering spam emails out of legal ones are instances of such problems. In such areas, traditional classification algorithms show function improperly, thus it is necessary to make use of novel algorithms that can tackle these problems. Among classification algorithms, decision trees have significant advantages such as being independent of any parameter and acting robust against outliers or unrelated attributes. Moreover, results of a decision tree are quite easy to interpret and extract rules from.... 

    Inverse Reinforcement Learning with Gaussian Processes

    , M.Sc. Thesis Sharif University of Technology Habibi, Beheshteh (Author) ; Sharifi Tabar, Mohsen (Supervisor)
    Inverse reinforcement learning (IRL) is one of the machine learning frameworks based on learning from humans; That is, instead of producing a decision process maximizing a predefined reward function, seeks to find the reward function based on the observed behavior of an agent. The biggest motivation of IRL is that, usually, determining a reward function for a problem is very difficult. We consider IRL in Markov decision processes; that is, the problem of extracting a reward function with the assumption of knowing the optimal behavior. IRL could be useful for apprenticeship learning to obtain skilled behavior, and for optimizing a reward function by a natural system. We first, determine a set... 

    General Reinforcement Learning

    , M.Sc. Thesis Sharif University of Technology Makiabadi, Nima (Author) ; Alishahi, Kasra (Supervisor)
    Reinforcement learning (RL) is a subfield of machine learning that expresses how to learn optimal actions in a wide range of unknown environments. Reinforcement learning problems are often phrased in terms of Markov decision processes (MDPs). However, being restricted to Markov environments to solve problems with limited state space is not an unreasonable assumption, but the main challenge is to consider these problems in as large a class of environments as possible, which includes any challenges that an agent may face in real world. Such agents are able to learn to play chess, wash dishes, invest in financial markets, and do many tasks that an intelligent human being can learn and do. In... 

    Iteration Control in Design Process

    , Ph.D. Dissertation Sharif University of Technology Soltan Mohammad, Bahram (Author) ; Malaek, Mohammad Bagher (Supervisor)
    The main goal of this research is to reduce aircraft design cycle period, by reducing the necessary number of design cycle iterations. The Design cycle period is one of the main characteristics of the design process and design cycle iterations play a major role in the design cycle period. To achieve the above mentioned goal, we present a mathematical model of iterations for the aircraft design process. This model describes the design coupled tasks as a discrete-linear time invariant dynamic system. This model also helps identify tasks which are the most important for generating iterations. This new method basically helps break information cycles that create iterations among important tasks.... 

    Applying MCDM to Evaluate Effectiveness of Wetlands Restoration Projects on Supplying Ecological Water Demand (Case study: Urmia Lake)

    , M.Sc. Thesis Sharif University of Technology Taghvaei Najib, Hamid Reza (Author) ; Tajrishy, Mohammad Masoud (Supervisor)
    Due to the numerous climate fluctuations and inefficient management of water resources during recent decades in Iran, the condition of some wetlands has become critical and the need for rehabilitation has increased. The importance of the wetlands and plains ecosystem have led to initiate some extensive projects to preserve and revive them. While implementing the projects some questions have been raised by the scientists and public whether the impact and success of these projects are in direct with objectives of the restoration program or not.For instance, Urmia Lake as one of the most precious natural habitats of Iran and as one of the biological reservoirs of the world is selected for this... 

    Application of Combining Multicriteria Decision Making Method for Decentralized Wastewater Treatment Plant Site Selection in Big Cities (Case Study: Tehran City)

    , M.Sc. Thesis Sharif University of Technology Neshastehgar, Mostafa (Author) ; Tajrishy, Masoud (Supervisor)
    One of the most important matters beside the shortage and requirement of water in big cities is how to dispose of wastewater. Also concerns with the continued use of centralized facilities include the capacity limitation, increased population growth, sustainable use of water, water shortages due to changes in global cycles and homeland security and disaster mitigation. Therefore the use of decentralized and satellite treatment systems is essential for big cities such as Tehran. One important matter pertaining to this issue is site selection of decentralized wastewater treatment plant. Multicriteria decision making is one of the methods that is used for site selection. By multicriteria... 

    Application of Data Mining Techniques in Diagnosis & Prediction of Heart Disease

    , M.Sc. Thesis Sharif University of Technology jahangiri, Sonia (Author) ; Akhavan Niaki, Taghi (Supervisor)
    Nowadays, data is the most important asset for health organizations in which the process of collecting, storing and analyzing of data leads to success of health organizations. Many companies have turned to data mining for the beneficial use of these data. The main purpose of data mining is to obtain useful knowledge from existing data. One of the diseases that is very significant for data miners is cardiovascular disease. Cardiovascular disease is the most important cause of death in the world. Therefore, it is necessary to improve the diagnostic and predictive measures of these patients. In this study, a database containing of characteristics of patients with chest pain who referred to... 

    Application of Game Theory in Stakeholder Management in Megaprojects; a Multiple Case Study

    , M.Sc. Thesis Sharif University of Technology Pourriahi, Houman (Author) ; Alvachi, Amin (Supervisor) ; Ghadimi, Behshad (Co-Supervisor)
    As the size and the scope of infrastructure projects have expanded, so has the array of stakeholders, either involved or affected. Such projects frequently take years to come together and develop over time through the efforts of project promoters and the participation of various stakeholders. Stakeholders through participation and input will help to legitimize and develop large scale project initiatives.This study used a longitudinal multiple case study approach that analyzed two tolled fixed crossing megaprojects. Activity research hits benchmarks before and after developments and shifts in participation strategies and stakeholders. Subsequently, we identify the main and key issues related... 

    Conditional Value-at-Risk Optimization Applications in Decision Making Problems

    , Ph.D. Dissertation Sharif University of Technology Eskandarzadeh, Saman (Author) ; Eshghi, Kourosh (Supervisor) ; Modarres Yazdi, Mohammad (Co-Advisor)
    In this thesis, the Conditional Value-at-Risk measure (CVaR) is used in two basic decision making problems under uncertainty. This measure is used previously in the field of risk management. The first problem is decision tree problem which is a multi-stage stochastic decision problem. In this problem, the risk of a decision maker is estimated by CVaR measure and a linear programming model is presented by using disjunctive programming theory. The importance of the developed model is in its generality for modeling all problems with decision tree structure. Then, its computational performance is compared to intuitive nonlinear programming models for the problem. Moreover, the presented model... 

    Career Decision Making Among Software Engineers: A Bounded Rationality perspective

    , M.Sc. Thesis Sharif University of Technology Shojai, Saeed (Author) ; Alavi, Babak (Supervisor)
    A qualitative study has been conducted in order to identify evidence of bounded rationality in software engineers' career decision making. Tversky and Kahneman's heuristics and biases approach has been used as a theoretical framework of the study. The theoretical framework comprised four decision-making and judgment heuristics, i.e. availability, representativeness, anchoring and adjustment, and affect heuristic. The data were gathered through semi-structured interviews and analyzed using thematic analysis method. The final results revealed that software engineers did make use of heuristics in making career decisions. Several incidents of the use of availability, representativeness, and... 

    Evaluation of Data Mining in Salinity Prediction and Evaporation Estimation

    , M.Sc. Thesis Sharif University of Technology Mahjoobi, Emad (Author) ; Agha Mohammad Hossein Tajrishi, Massoud (Supervisor)
    Since physical variables are almost dependent, uncertain and have significant time and spatial changes, nature of hydrological and environmental systems is so complicated, nonlinear and dynamic. Many models have been developed for studying and analyzing various phenomena in these systems. Recently data mining approaches have been used as new methods for modeling of complicated engineering systems. In this study, performance of several data mining tools in analyzing two phenomena in water quality management have been evaluated. These algorithms are Multilayer Perceptron Neural Network (MLP), Radial Basis Function Neural Network (RBFN), Support Vector Machines (SVMs) in the field of Artificial... 

    Usage of Data Mining for Prediction of Customer Loyalty

    , M.Sc. Thesis Sharif University of Technology Salehi, Reza (Author) ; Rafiee, Majid (Supervisor)
    Markets are becoming more saturated every day and competition between different businesses is increasing. The importance of managing Customer churn in various businesses has become increasingly important because the cost of attracting a new customer is many times greater than retaining an existing customer. With the development of data mining and its increasing expansion and the other side, the increase of stored information related to various organizations and businesses has accelerated the operations of extracting knowledge from data. Today, businesses are moving towards the use of intelligent knowledge extraction systems, of which Customer churn prediction systems are one of the most... 

    Forecasting Residential Natural Gas Consumption in Tehran Using Machine Learning Methods

    , M.Sc. Thesis Sharif University of Technology Khazaei, Armin (Author) ; Maleki, Abbas (Supervisor)
    According to increasing energy demand in Iran and the world, the role of natural gas as a relatively clean and cost-effective source has received more attention. Given the high share of the residential sector in the country's natural gas consumption, providing a model for forecasting the demand of this sector is of great importance for policy makers and decision makers in this field. In the present study, we employ three popular methods of machine learning, support vector regression, artificial neural network and decision tree to predict the consumption of natural gas in the residential sector in Tehran according to meteorological parameters (including temperature, precipitation and wind...