Sharif Digital Repository

A solution to the imbalance of vehicles in one-way carsharing systems is vehicle relocation which involves staff members to redistribute the vehicles between stations. Vehicle relocation, however, can lead to an imbalance of staff members between stations. Thus, staff members, themselves, need to be relocated between stations to perform the vehicle relocations. This study addresses the joint optimization of vehicle relocation and staff rebalancing using two integrated multi-traveling salesman formulations. Results show that fleet size is more sensitive to demand than staff size, staff size is inversely related to vehicle cost, and that vehicle relocation time increases with vehicle cost  

Nowadays the application of decision support systems (DSSs) in process safety is more important than ever. The use of DSS for preventing domino effects is one of the diverse applications of these computer-automated toolkits. Different software packages were developed in recent years, each trying to manage domino risk by a specific approach. In this chapter, the definition, architecture, benefits and essential characteristics of DSS toolkits are described. The application, scope, approach, technical features, advantages, shortcomings and limitations of all the available computerized tools and software packages presented up to now for managing domino effect are then discussed and analyzed... 

In a gas transmission network (GTN), faults can easily propagate due to the interconnections of streams. The main objective of this paper is to develop a systematic framework for an online decision support system (DSS) in order to make the right decisions to get the GTN out of critical conditions (which cannot be handled by the plant controllers) smoothly. One of the key features of the proposed scheme is its lack of dependence on prior knowledge of the fault signals (e.g., number of faults, and their origin). In this article, the GTN is modeled by a fuzzy directed graph (FDG). The proposed approach utilizes a reasoning algorithm based on the deviations that exist in the process variables... 

With thousands of new questions posted every day on popular Q&A websites, there is a need for automated and accurate software solutions to replace manual moderation. In this paper, we address the critical drawbacks of crowdsourcing moderation actions in Q&A communities and demonstrate the ability to automate moderation using the latest machine learning models. From a technical point, we propose a multi-view approach that generates three distinct feature groups that examine a question from three different perspectives: 1) question-related features extracted using a BERT-based regression model; 2) context-related features extracted using a named-entity-recognition model; and 3) general lexical... 

Systematic management of enterprise knowledge, e.g. new ideas, innovations and patents, has a great impact on business sustainability and growth. Without comprehensive assessment of knowledge assets, agile companies can not design and run knowledge promotion programs required for survival in competitive environments in modern economy. A comprehensive framework for the assessment of as-is situation and development of knowledge promotion plans includes (a) assessing the as-is situation- the quantity and quality of organizational knowledge; (b) developing a situational program based on assessment results, business strategy and knowledge maturity indicators; (c) and working out an action plan in... 

Recent challenges have brought about an inevitable tendency for enterprises to lunge towards organizing their information activities in a comprehensive way. In this respect, Enterprise Architecture (EA) has proven to be the leading option for development and maintenance of information systems. EA clearly provides a thorough outline of the whole information system comprising an enterprise. To establish such an outline, a logical framework needs to be laid upon the entire information system. Zachman framework (ZF) has been widely accepted as a standard scheme for identifying and organizing descriptive representations that have critical roles in enterprise management and system development. In... 

Considering the wide spread locations of wind farms in Iran, it is important to develop a suitable decision support system (DSS) to fulfill proper management of wind farms. Extensive literature survey indicates that there are no integrated forms of DSS to manage a set of wind farms. The existing wind farms are performing independently, and there is no practical method for exchanging the online data. DSS can contribute to optimal operation of wind farms, operation and maintenance scheduling, pricing policy, etc. In this study, a geographic information system and RETSCREEN software were linked to the designed DSS to achieve a more suitable result. Also, a huge number of data are constantly... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

Cloud Computing has become popular nowadays. Cloud providers with scalable infrastructures can offer cloud-based services which reduce investment of organizations and diminish most of their operational costs. Therefore, traditional services need to be renovated in the spirit of cloud environments. In this paper, Decision Support-as-a-Service (DSaaS) which is a cloud-based decision support system is introduced. The DSaaS can help managers to make fast and precise decisions. Also, the important challenges of such a system are discussed and a proper energy-aware resource allocation policy is proposed as the solution for the main challenge. A wide range of simulation results show that the policy... 

In software systems development lifecycle making use of software architecture, especially by taking advantage of architecture styles and patterns, is an essential part which increases product's quality. Nowadays, in order to cover complexity of systems, combination of different architecture styles should be used; therefore ambiguous behaviors might occur. Hence, due to the critical need for toolsets capable of selecting suitable styles and patterns, an environment is proposed in this paper which can perfectly cover different aspects of the implementation of decision support system (DSS). The designed environment obviates data implementation concepts and security considerations. Moreover, it... 

Considering the wide spread locations of wind farms in Iran, it is important to develop a suitable decision support system (DSS) to fulfill proper management of wind farms. Extensive literature survey indicates that there are no integrated forms of DSS to manage a set of wind farms. The existing wind farms are performing independently, and there is no practical method for exchanging the online data. DSS can contribute to optimal operation of wind farms, operation and maintenance scheduling, pricing policy, etc. In this study, a geographic information system and RETSCREEN software were linked to the designed DSS to achieve a more suitable result. Also, a huge number of data are constantly... 

Applications in pervasive computing environment exploit information about the context of use, such as the location, tasks and preferences of the user, in order to adapt their behavior in response to changing operating environments and user requirements. Utilizing context with aid of ontology in data and model, decision support systems can provide better and more desirable support to their users. The effects and advantages of exploiting ontology in user modeling and DSS is discussed. We propose a framework of a Ontology-based Decision Support System (O2DSS), including ontology in model base, database and their advantages. © 2008 IEEE  

Fuzzy logic is a powerful problem-solving methodology that provides a remarkably simple way to draw definite conclusions from vague, ambiguous or imprecise information. This study is a review on the possibility of developing a tool to help site managers and planners in selecting the most suitable actions for construction productivity improvement in a complex construction site, using fuzzy logic theory. Improving productivity can have a large impact on the overall construction process and consequently result in significant time and cost savings, i.e. minimizing capital cost on the construction projects. Problems associated with productivity measurement such as "lack of a standard productivity... 

Demand forecasting plays an important role as a decision support tool in power system management, especially in smart grid and liberalized power market. In this paper, a demand forecasting method is presented by using support vector regression (SVR). The proposed method is applied to practical hourly data of the Greater Tehran Electricity Distribution Company. The SVR parameters are selected by using a grid optimization process and an investigation on different kernel functions. Moreover, correlation analysis is used to find exogenous variables. Acceptable accuracy of load prediction is shown by comparing the result of SVR model to that of the artificial neural networks and the actual data,... 

On-line analytical processing (OLAP) is a mature technology as a part of the new category named Business Intelligence for decision supports that are given to managers to analyze different dimensions of multidimensional data and enable them to obtain competitive advantage by accurate analysis and examination of organizational data. So considering the factors affecting the user's acceptance and use are important to increase the benefits of such systems. The study has used Technology Acceptance Model (Davis 1989) to determine technology acceptance of an Online Analytical Processing (OLAP) in Tarbiat Modares University. This study took advantage of Structural Equation Modeling (SEM) approach to... 

This article deals with technology strategy and its linkage with overall strategy at multi-business, diversified groups. In the last two decades, the alignment of technology and business strategy has been one of the important research fields in strategy and technology management scopes. These researchs has been concentrated on single companies through which different frameworks, models & decision support tools have been developed and widely utilized by industries. Although multi-business and diversified groups play an important role in global and national economics and need a comprehensive and overall plan for the management of their diversified technological assets, there are few researchs... 

Outpatient appointment scheduling problems have recently gained increasing attention. This paper provides a comprehensive review of recent analytical and numerical optimization studies that present decision-support tools for designing and planning outpatient appointment systems (OASs). A structure for organizing the recent literature according to various criteria is provided, including a framework that classifies decisions at the strategic, tactical, and operational levels. The OAS literature is evaluated from four perspectives: problem settings, environmental factors, modeling approaches, and solution methods. In addition, research gaps and areas of opportunity for future research are... 

Noise is one of the most important sources of pollution in the metropolitan areas. The recognition of road traffic noise as one of the main sources of environmental pollution has led to develop models that enable us to predict noise level from fundamental variables. Traffic noise prediction models are required as aids in the design of roads and sometimes in the assessment of existing, or envisaged changes in, traffic noise conditions. The purpose of this study was to design a prediction road traffic noise model from traffic variables and conditions of transportation in Iran. This paper is the result of a research conducted in the city of Hamadan with the ultimate objective of setting up a...