Sharif Digital Repository

The purpose of this study is to present a suitable model for calculating the costs imposed on society due to deaths and injuries due to infrastructure failure due to earthquakes, which is used in the analysis of community resilience. Much research has been done to date to calculate the economic costs of infrastructure failure. However, no suitable analytical framework has been provided to quantify the costs of deaths and injuries to people due to earthquake failure. Previous research has provided methods such as the value of statistical life to quantify the social costs caused by accidents and environmental pollution. However, the literature review results in the field of seismic resilience... 

Facility Layout Problem (FLP) is known as one of the classical problems in industrial engineering which have acquired high attractiveness to researchers. Therefore, in this study, a practical mathematical model is formulated and solved
In order to have a real and practical model, robust optimization is applied to FLP. Therefore, it is supposed to have dynamic values for departments' dimensions. This assumption is very critical to generate an effective and acceptable layout. We consider that each dimension of a department can be changed in a given interval. Due to this assumption, we introduce two new parameters which are called width and length deviation coefficients, respectively.... 

Regarding recent progress in the field of decision theory and the discovery of the important factors in human decision making, it is suggested by researchers to build up models that take all of, or at least most of, those factors into account simultaneously. In this research, first, we present some important achievements in the field of decision theory then develop a model based on these factors. Therefore, we focus on influential factors in human decision making, especially recent ones in neuroeconomics and mathematical models are presented to describe their effects. Then a descriptive model is proposed and changed it to a prescriptive model by adding some assumptions and standard charts.... 

Among scientific fields of study, mathematical programming has high status and its importance has led researchers to develop accurate models and effective solving approaches to addressing optimization problems. In particular, meta-heuristic algorithms are approximate methods for solving optimization problems whereby good (not necessarily optimum) solutions can be generated via their implementation. In this study, we propose a population-based meta-heuristic algorithm according to chemotherapy method to cure cancers that mainly search the infeasible region. As in chemotherapy, Chemotherapy Science Algorithm (CSA) tries to kill inappropriate solutions (cancers and bad cells of the human body);... 

Peoples need financial resources to improve their quality of life, and companies need them to progress and increase their comparative advantage. Borrowing is one of the most popular methods of financing. Peer-to-peer lending, also known as "marketplace" or "social" lending, is a novel form of intermediation that expunges the role of financial institutions (like banks) as an intermediary and allows entities (individuals or businesses) to raise loans directly from other entities. This lending platform can provide better quality services to borrowers (by quickly providing a simple loan application process through a transparent and flexible portal) and lenders (by managing their funding and live... 

This study offers a framework to manage mass vaccination programs in response to an outbreak in a city. Compared to previous studies, we consider more operational challenges in the vaccination process; for example, transshipment between vaccinations units and availability of second doses. Our objective function is based on the risk of unvaccinated individuals. Therefore, the model aims at favoring those places in the city where the risk of unvaccinated people is high. Using different kinds of vaccines is another factor that our mathematical model includes. Vaccines are categorized into single-dose and double-dose classes. In this regard, the balanced access to different vaccine types is of... 

Based on fog computing paradigm, new applications have become feasible through the use of hardware capabilities of smart phones. Many of these applications require a vast amount of computing and real-time execution should be guaranteed. Based on fog computing, in order to solve these problems in is necessary to offload heavy computing to servers with adequate hardware capabilities. On the other side, the offloading process causes time overhead and endangers the real-timeliness of the application. Also, because of the limited battery capacity of the handheld devices, energy consumption is very important and should be minimized.The usual proposed solution for this problem is to refactor the... 

Investors highly value the ability to predict the behavior of the capital market. Over time, various methods have been introduced to forecast the future of this market and anticipate its movements. A novel approach to achieving this is by developing data-driven decision support systems that can assist investors in making informed trading decisions. The opinions of experts play a crucial role in shaping people's perception of the market, which ultimately affects its final behavior. In this study, we have created a decision support system that can help investors by considering the complexities and meaningful relationships between different aspects of the problem. We have developed frameworks... 

Transportation Network Companies (TNC) like Snap and Tap30 are ride sharing platforms that connect drivers and passengers in real time using simple mobile phone applications. The most interesting feature of these platforms is that they do not hire drivers and allow them to choose when and where to offer a ride. Dynamic and fluctuating supply and demand, the necessity to forecast the changes, implementing them in ride pricing and driver-passenger assessment are considered as important challenges for such systems. In this research, first, we want to analyze the spatial structure of TNCs and then forecast network changes more precisely. The method used for forecasting is LASSO which is a... 

Real-world decision-making problems usually have several criteria for evaluating the performance of alternatives. On the other hand, mathematical programming is a very practical tool for modeling and solving decision-making problems and multi-objective mathematical programming has high importance among researchers and managers in this field of study. However, the field of multi-objective integer programming is considered a rigorous category. Methods for solving these types of problems can be divided into three different approaches. There are few approaches and methods for solving multi-objective mixed-integer optimization problems in litreture.In this research, an extension of benders... 

Today, the correct management of construction projects in IRAN's water industry has become a severe concern for its managers. Construction projects of the water industry constitute a considerable part of the country's construction industry. Several significant Issues such as operation management, water industry projects, correct management of resources, crisis management in the water industry, increased productivity and useful life of structures, increasing productivity, and preventing water loss are among the determinative challenges in construction projects in Iran. One of the new methods for the correct management of the life cycle of projects in this area is the use of Building... 

Video games with respect to an ever Increasing player pool and Industry growth, have attracted a lot of attention in recent years. Dota 2, as one of the most successful games both in casual gamers’ community and E-sport community, is considered as a proper case study, however, most of the research done was limited to predicting games’ outcome. Despite The popularity, the rather unintelligent AI of the game has made quite a frustrating experience for new players. In this research, with a novel approach, hero features are used to predict their future positions. For this purpose, 35 professional games are collected and analyzed and 601 features are extracted. Then, suitable features are... 

Stock price patterns are a technical analysis approach to forecast future trends with tremendous practical benefits. However, the current algorithms solely rely on machine learning techniques and deep neural networks which could be a problem in countries where data sets such as these are not available. We propose an algorithm based on geometry and mathematics for this problem, leading to an O(n^3logn + n^2k) complexity, where k is the number of triangular patterns  

The municipality is an administrative, public and non-state institution that falls into the city district of the most countries’ administrative divisions. This institution has relatively autonomy and independent power. Municipalities are trying to apply the best approaches (Such as Building Information Modeling (BIM) as a procedure contributing the project management) to save time and money, as well as to satisfy the citizens in the implementation of civil projects. This study examines and evaluates the readiness of municipalities to modify the construction projects based on BIM. In addition, a pattern for identifying BIM applications, evaluating the organization readiness and the needs of... 

The competition for staying in the business world has intensified today with the rise of open-source and commercial software. As long as a software is tailor-made to suit the needs of users, it is so-called alive and can stay in the competition. So the maintenance phase is necessary to make changes to the software to meet the needs of users. To reduce costs associated with this phase, it is necessary to avoid software bugs. One way to avoid software bugs is to use peer code review. Peer code review has been recognized as one of the best software engineering principles of the last 35 years. This principle helps maintain the quality of the code due to changes made to parts of the code that... 

Deep learning algorithms combined with supervision rely heavily on labeled data, posing challenges in the data labeling process. Addressing this issue, researchers in the field of machine learning have focused on developing approaches to reduce the dependency on labeled data and improve the efficiency of data collection for labeling purposes. This thesis investigates the training of a classification model using data collected through a human-in-the-loop system. Notably, this research pioneers the application of active learning techniques to differentiate between political and non-political Persian tweets. The dataset introduced in this study is the sole available collection for this specific... 

One of the most significant factors for the on-time and successful implementation of construction projects is contract management. Proper management of construction contracts and assessment of potential risks in the bidding process and before its signing have a significant impact on preventing or reducing the occurrence of claims and disputes between the contract parties at various stages of the project. In this research, using the latest deep learning (DL) and natural language processing (NLP) state-of-the-art methods, and various deep neural networks (DNN) architectures a model has been developed for extracting Persian contract risk-prone clauses. In addition, this study provides a...