Sharif Digital Repository

With the development of online two-sided platforms and increasing competition between these companies, issues such as customer targeting or recommendation systems have become more important to organizations. So far, various tools have been used for this purpose, but one of the most effective methods is the data analytics based on the stored data, through which personalized promotions can be automatically sent to the customers by implementing optimization models and algorithms. In this research, we present a model that re-adjust the commissions received from drivers based on detecting hidden patterns in their behavior in order to maximize the company's profit and then offer a suitable... 

Control charts are one of the most important tools in statistical process control to detect assignable causes. The goal of a control chart is to detect an out-of-control state quickly so that process engineers can initiate their search for the special cause sooner. Once the special cause has been identified, the appropriate action can then be taken to improve the process.A new method to estimate the change point of Poisson rate parameter when the step change occurs is proposed in this thesis. That is, the rate parameter is assumed to suddenly shift from its in-control value to an out-of control value at a single unknown point in the process.To do this, a belief that the process is in-control... 

Road accidents are unfortunate events that cause more thanl16000 deaths each year in Iran. Intercity accidents require a comprehensive plan to reduce casualties because the number of roads users are increasing and the accidents account for nearlyl65% of fatalities. In this study, we first tried to identify the status of Iran through a study of traffic accidents in the world, and then the research and activities carried out in Iran were analyzed to find new and effective solutions. Using the daily fatalities data froml2008 tol2014, and using the new methodology presented in this research based on the Discrete Fourier Transformation (DFT), the Box-Jenkins models and the Secant method, the... 

Today we live in an era of continuous technology improvement which results in huge changes in different areas of diverse industries. Among the most recent systems for monitoring and quality control which benefits from high speed, are machine vision systems. The output of these systems, are digital images that can be used for monitoring instead of the original products. Unfortunately due to the computational complexity of data extracted from the digital images, traditional methods lose their efficiency. Therefore, in this thesis, a method is proposed to design a model for the monitoring and control of image-based processes, which uses classification methods, that are capable of classifying... 

In this research, it has been tried to use deep learning methods and embedding vector, in addition to user-item data, from user side information such as age, gender, city, etc., and also for item information such as product name, product category, etc. can be used to better understand customer behavior patterns and provide a relatively rich recommender system. The proposed model in this research has two phases, the first phase tries to identify the user and item feature vector and form the user similarity matrix and the user-item correlation matrix. The outputs of phase one are used as inputs of phase two. In the second phase of the model, using these inputs, Top-N recommendation are... 

In modern industries, multivariate multistage auto-correlated processes are widely used to ensure productivity and product quality. Interconnections between work stations bring a challenging task in detecting various shifts and identifying their root causes. In addition, simultaneous monitoring process mean and variability with single control chart methods has gained considerable attention throughout these years. In this article, a double-max multivariate exponentially weighted moving average (DM-MEWMA) chart is proposed based on two novel statistics to monitor the parameters of multivariate multistage auto-correlated processes jointly. Prior knowledge of variation propagation has been used... 

What people write about their experience on web pages or social media about a product they have used or a service they have received can influence the reputation and the popularity of a certain brand with a great deal. If the reviews that exist about a product or a service of a certain company are mainly positive, it can increase the profit and improve the image of the company. On the other hand, mostly negative reviews can decrease the profit and destroy a company's image irreversibly. Unfortunately, because of this great influence that online reviews have over general public's decision to use a a product or a service of a brand, some companies hire people to write undeserving positive... 

Over the past few decades, with the exponential increase in data volume, scientists and researchers have tried to discover relationships and algorithms for productivity and find useful information from this amount of data in various fields. Their efforts in data analysis have led to the development of algorithms in the big data field. The result of researchers' working in multiple fields has come to aid the people of science and technology. Among the most important of these areas, we can mention the health and medical sectors, financial sectors, services, manufacturing sectors, etc. The purpose of this study is to enter the financial industry and use data mining tools. One of the newest and... 

Control chart is one of the most powerful tools in statistical process control (SPC). This tool has been widely used in industrial schemes; however, in recent years, it has become widespread in health care studies as well. Most of these studies are dealing with monitoring qualitative variables in one-stage processes. This research presents a new mechanism for monitoring medical processes, by modelling the bone marrow transplant surgery as a dependent multi-stage process into a multiple profile. In this mechanism, the characteristics which will be monitored are quantitative, and the cascade property between stages is considered. Moreover, risk adjustment methods have been used due to the... 

Water demand forecasting and modeling is very important and needful in water resource planning and management as well as water consumption forecasting. The forecasting helps the managers to design and operate various infrastructures of water supply such as tanks and other distribution equipments. Nowadays, intelligent systems are very efficient and practical tools because of their high ability in forecasting and independency from limitative assumptions in classic methods. In this thesis, one of the newest methods, called support vector regression method, is used to forecast monthly demands of water consumption in Tehran, Iran. To develop the method, data is first preprocessed through... 

Today with the development of technology in medical science, there is a need to develop new methods to analyze and process the medical images. Furthermore, increasing use of machines and computers to accomplish prediction goals delineates that these tools had promising results. Because of all the above, this research focuses on processing and analyzing medical images with using data mining tools in order to identify MS and tumor disease which have been ubiquitous in last decades, fast and meticulous. To do so, we introduce a new clustering algorithm based on the modularity measure of graph networks as well as a new machine learning algorithm based on Kalman filter for Tensor-based data.... 

In a production process, when the quality of a product depends on more than one characteristic, and there is correlation between them, using univariate control charts increases type І and type ΙΙ errors. So for monitoring these processes, multivariate quality control charts are used. Multivariate statistical process control is receiving increased attention in the literature,but little work has been done to deal with multi-attribute processes and just in recent years some techniques are developed in this field. In this thesis, based on the power transformation concept, two new techniques have been developed to monitor multi-attribute processes, in which the defect counts are important. In the... 

In this research, a new Bayesian method for constructing confidence intervals on the parameters of any continuous distribution is first developed. The main idea behind developing this method is to model uncertainty. As an application of the proposed methodology, confidence intervals for the two parameters of the Weibull distribution along with their joint confidence interval are then derived in which data can be of type I censored data, type II censored data or uncensored. The new confidence intervals are next compared to other existing exact confidence intervals in the literature and shown to have better performances. Furthermore, we show the lengths of the existing exact confidence... 

This study proposes a deep reinforcement learning approach to solve a perishable inventory allocation problem in a two-echelon supply chain. The inventory allocation problem is studied considering the stochastic nature of demand and supply. The examined supply chain includes two retailers and one distribution center (DC) under a vendor-managed inventory (VMI) system. This research aims to minimize the wastages and shortages occurring at the retailer's sites in the examined supply chain. With regard to continuous action space in the considered inventory allocation problem, the Advantage Actor-Critic algorithm is implemented to solve the problem. Numerical experiments are implemented on... 

A common decision in project management is the selection of contractors to simultaneously optimize three objectives of the project’s triangle. This issue becomes more important if there is more monetary value involved or there is limited number of capable contractors. In project planning, there is numerous choices for tasks; each with specific time, cost and quality. There is no trade-off problem, if one of the choices has the best time, cost, and quality, simultaneously. However, as these criteria do not generally work in a unique direction, it makes the selection decision difficult. A contractor who performs the projects on time may have higher cost and lower quality. Given that there is a... 

Emergence of crypto-currency and blockchain technology revolutionize supply chain processes. In addition, customer needs for more information on products or services from origin to destination, highlights the necessity of transparency, originality and traceability in supply chains. This research is aimed to develop a blockchain based system ascertaining supply chain transparency and originality. To this aim, a joint pricing and closed-loop supply chain network design problem is selected as a good platform to implement it. Due to increasing concerns on environmental issues and maximizing job opportunities, sustainability is also considered in the proposed problem. To ascertain transparency... 

One of the most trivial factors for every service company is to fulfill customer demands and to satisfy them. For this purpose, it is needed to explore the business fundamentals. Transportation companies, however seem to be more important, because in one hand, the demand for their services is too many. In the other hand due to the intense competition between rivals, every business tries to stand in the crowd; thus, it is of high importance to correctly predict the travel time as well as fare. The importance of time is not only because of having a fare pricing system, but also it is important for scheduling, assigning drivers, and covering city or a particular district. Travel time... 

In this thesis the simulation optimization problems are solved by using Artificial Bee Colony (ABC). The main objective is to improve and adapt the ABC algorithm for solving the optimization problems in deterministic and stochastic environments. For solving deterministic problems, directed search in neighborhood and Nelder-Mead algorithm are combined with ABC algorithm to improve the convergence rate and solutions. Moreover; in stochastic environment, hypothesis test and Kim-Nelson (KN) indifference zone ranking and selection procedure are helping bees to produce solutions with better confidence level on the quality of the solution. Results of optimizing an extensive complex benchmark... 

Intensity-modulated radiation therapy is a well-known technique to treat cancer patients worldwide. A treatment plan in this technique requires decision-making for three main problems: selection of beam angles, intensity map calculation, and leaf sequencing. Previous works have investigated these problems sequentially. In this research, we present a new integrated framework for simultaneous decision-making of directions, intensities, and apertures shape, called direct angle and aperture optimization, and develop a mixed-integer nonlinear mathematical model for the problem. At first, the problem's single-objective model is established using the quadratic dose penalty function. After that,... 

This study investigates optimal strategies for price, warranty length and production rate of a new product to maximize profit of a producer during lifecycle of the product. We consider both durable products and non-durable ones. Customers buy non-durable products many times but if we consider the planning horizon relatively short, each customer buys one product during the period. So, the market for non-durable products is static and for durable ones is dynamic. The objective function includes both demand and cost functions, where production cost, warranty cost and inventory costs are involved. A solution approach using the maximum principle is described and some propositions are discussed...