A query processing system for very large spatial databases using a new map algebra

Dans cette thèse nous introduisons une approche de traitement de requêtes pour des bases de donnée spatiales. Nous expliquons aussi les concepts principaux que nous avons défini et développé: une algèbre spatiale et une approche à base de graphe utilisée dans l'optimisateur. L'algèbre spatiale est défini pour exprimer les requêtes et les règles de transformation pendant les différentes étapes de l'optimisation de requêtes. Nous avons essayé de définir l'algèbre la plus complète que possible pour couvrir une grande variété d'application. L'opérateur algébrique reçoit et produit seulement des carte. Les fonctions reçoivent des cartes et produisent des scalaires ou des objets. L'optimisateur reçoit la requête en expression algébrique et produit un QEP (Query Evaluation Plan) efficace dans deux étapes: génération de QEG (Query Evaluation Graph) et génération de QEP. Dans première étape un graphe (QEG) équivalent de l'expression algébrique est produit. Les règles de transformation sont utilisées pour transformer le graphe a un équivalent plus efficace. Dans deuxième étape un QEP est produit de QEG passé de l'étape précédente. Le QEP est un ensemble des opérations primitives consécutives qui produit les résultats finals (la réponse finale de la requête soumise au base de donnée). Nous avons implémenté l'optimisateur, un générateur de requête spatiale aléatoire, et une base de donnée simulée. La base de donnée spatiale simulée est un ensemble de fonctions pour simuler des opérations spatiales primitives. Les requêtes aléatoires sont soumis à l'optimisateur. Les QEPs générées sont soumis au simulateur de base de données spatiale. Les résultats expérimentaux sont utilisés pour discuter les performances et les caractéristiques de l'optimisateur.Abstract: In this thesis we introduce a query processing approach for spatial databases and explain the main concepts we defined and developed: a spatial algebra and a graph based approach used in the optimizer. The spatial algebra was defined to express queries and transformation rules during different steps of the query optimization. To cover a vast variety of potential applications, we tried to define the algebra as complete as possible. The algebra looks at the spatial data as maps of spatial objects. The algebraic operators act on the maps and result in new maps. Aggregate functions can act on maps and objects and produce objects or basic values (characters, numbers, etc.). The optimizer receives the query in algebraic expression and produces one efficient QEP (Query Evaluation Plan) through two main consecutive blocks: QEG (Query Evaluation Graph) generation and QEP generation. In QEG generation we construct a graph equivalent of the algebraic expression and then apply graph transformation rules to produce one efficient QEG. In QEP generation we receive the efficient QEG and do predicate ordering and approximation and then generate the efficient QEP. The QEP is a set of consecutive phases that must be executed in the specified order. Each phase consist of one or more primitive operations. All primitive operations that are in the same phase can be executed in parallel. We implemented the optimizer, a randomly spatial query generator and a simulated spatial database. The query generator produces random queries for the purpose of testing the optimizer. The simulated spatial database is a set of functions to simulate primitive spatial operations. They return the cost of the corresponding primitive operation according to input parameters. We put randomly generated queries to the optimizer, got the generated QEPs and put them to the spatial database simulator. We used the experimental results to discuss on the optimizer characteristics and performance. The optimizer was designed for databases with a very large number of spatial objects nevertheless most of the concepts we used can be applied to all spatial information systems."--Résumé abrégé par UMI

A decision support method for selecting design and manufacturing alternatives

One of the most important decisions which should be made at the early stage of the design process is to select one design alternative. Not only should the decision be made by tradeoffs between different conflicting criteria of the single stakeholder but also to aggregate different outcomes obtained by multiple stakeholders. This thesis represents a decision support tool for selecting design alternatives, in which a single choice has to be made between a number of alternatives in the presence of single or multiple stakeholders, multiple conflicting criteria, and resource limitation, based on two routes: using Analytic Hierarchy Process (AHP) alone and the combination of AHP with Zero-One Goal Programming (ZOGP). Using AHP-ZOGP allows the concept-concept and concept-specification approaches to be considered simultaneously in order to improve the process of concept design selections. Different outcomes obtained by using AHP alone, can be aggregated by two heuristic methods based on distance function, to generate an index for final single selection. The first method uses the final weights obtained by AHP, while the second method uses its detailed weights. AHP weights are then used to construct the ZOGP's objective function and constraints' parameters of intangible criteria for each individual stakeholder. Another ZOGP model can be constructed to aggregate the different outcomes, obtained by individual ZOGP's models, based on combining their objective functions. The advantages of using aggregated ZOGP models in comparison with heuristic methods are, not only ZOGP aggregated model is able to minimise the undesirable distances between sub-criteria and Product Design Specification (PDS), but also it can take into account the resource limitations explicitly. The case studies, which involved vehicle manufacturing technology selection, choosing a peristaltic pump, selection of a swivel joint design, and the justification of advanced manufacturing systems, possessed the characteristics of the type of problems this tool is intended to support. The case studies showed how it is possible to consider many criteria from different stakeholders to yield a single outcome that covers the requirements of those stakeholders

A query processing system for very large spatial databases using a new map algebra

In this thesis we introduce a query processing approach for spatial databases and explain the main concepts we defined and developed: a spatial algebra and a graph based approach used in the optimizer. The spatial algebra was defined to express queries and transformation rules during different steps of the query optimization. To cover a vast variety of potential applications, we tried to define the algebra as complete as possible. The algebra looks at the spatial data as maps of spatial objects. The algebraic operators act on the maps and result in new maps. Aggregate functions can act on maps and objects and produce objects or basic values (characters, numbers, etc.). The optimizer receives the query in algebraic expression and produces one efficient QEP (Query Evaluation Plan) through two main consecutive blocks: QEG (Query Evaluation Graph) generation and QEP generation. In QEG generation we construct a graph equivalent of the algebraic expression and then apply graph transformation rules to produce one efficient QEG. In QEP generation we receive the efficient QEG and do predicate ordering and approximation and then generate the efficient QEP. The QEP is a set of consecutive phases that must be executed in the specified order. Each phase consist of one or more primitive operations. All primitive operations that are in the same phase can be executed in parallel. We implemented the optimizer, a randomly spatial query generator and a simulated spatial database. The query generator produces random queries for the purpose of testing the optimizer. The simulated spatial database is a set of functions to simulate primitive spatial operations. They return the cost of the corresponding primitive operation according to input parameters. We put randomly generated queries to the optimizer, got the generated QEPs and put them to the spatial database simulator. We used the experimental results to discuss on the optimizer characteristics and performance. The optimizer was designed for databases with a very large number of spatial objects nevertheless most of the concepts we used can be applied to all spatial information systems."--Résumé abrégé par UMI

An Integrated Methodology for Strategic Selection Problems

Strategic selection problem is a multi-criteria problem which includes conflicting tangible and intangible criteria. In order to select the most appropriate strategic alternative it is necessary to make tradeoffs between these criteria as well as taking into account the resource limitations which may exist. Available methods neglect the distance concept which exists between the alternatives weights with regard to a single criterion and its target value. In this paper in addition to applying the Analytical Hierarchy Process (AHP) as a stand-alone methodology an integration of the AHP and Zero One Goal Programming (ZOGP) is proposed. In this integration each single criterion viewed as a constraint in a ZOGP model which enable the model to take into account not only the distances but also to consider the real resource limitation for tangible criteria. In order to justify the methodology, it is applied to selection of Advanced Manufacturing Systems (AMS

Evaluation and Selection of International Supplier, Underscoring Risk Factors

This paper evaluates the decision making process for import complete manufactured pieces versus import of partial pieces to assemble in Iran, taking into account the risk factors for a manufacturing company. Since this sort of decision making confront with several risks, it is necessary to establish a process for finding the risks associated with this kind of problems in order to decrease the effects of these risks in the process. Since the problem is classified as a Multiple Criteria Decision Making (MCDM) problem, Uncertain Analytical Hierarchy Process (UAHP) was used to find the most attractive alternative. Because the alternatives were identified from the first point, a bottom-up procedure was used to organize the hierarchy. In initial stage, the attributes which distinct from the alternatives were obtained by literature review and experts' interviews. Then the attributes were grouped to upper level to establish the criteria. Three criteria were found from this stage. The criteria were product, partners, and environment which they encompassed 12 attributes. Forming the hierarchy and doing the uncertain pairwised comparisons, which considers a range of numbers instead of one single number for declaring the preference between two factors, a Linear Programming (LP) model with two types of objective functions were formed for each individual alternative. Each single LP model can express the maximum and minimum value of each individual alternative. The research's results indicate the most appropriate alternative is to import the final product from India. The last preferred one was to import the parts of the final product from India. This study can be a suitable framework in supply chain management and purchasing decisions and risk evaluations because the major parts of manufacturing activities is always to decide about the selection of most preferred strategies for companies

Prioritizing of Strategy Implementation Obstacles among Energy sector's Contractors Using Fuzzy TOPSIS Method

The main purpose of this practical survey is devoted to identify the obstacles of strategic plan implementation among energy sector's contractors and then, to present a classification of identified obstacles on the basis of their priorities. In order to achieve this purpose, 8 factors were chosen as the obstacles of strategic plans in energy sector following the literature review and experts comments, and then applied to 87 managers and senior experts of strategic planning in contracting firms by a questionnaire. The Fuzzy TOPSIS technique is assumed as a well-known Multiple-criteria Decision Making (MCDM) approach. Results showed that organizational structure was received the most priority as an obstacle in implementing strategic plan in contracting industry and operational planning, resource allocation, quality of strategy, communication, strategy executors, control and commitment got subsequent ranks. So, findings of this survey could improve the efficiency of contracting firm's managers to direct the process of strategy implementation and to overcome on identified obstacle

Provide a Mathematical Model for Financing Small and Medium-Sized Manufacturing Enterprises (SMEs) in the Supply Chain

Given the importance of financing small and medium-sized manufacturing companies in order to provide working capital and their profitability, this study has presented a mathematical model for financing these companies by factoring in the supply chain. Factoring is one of the most important ways to finance the business world, especially for small and medium-sized enterprises. Therefore, considering the relationship between the enterprise and the bank, suppliers and buyers based on the integration of financial and physical flows in the supply chain, this research has financed the enterprise in the above-mentioned method. In order to analyze the validity of financing methods, goals, parameters and important variables in modeling, the perspective of experts based on the index of content validity ratio has been used. The goals of modeling are to maximize profits and achieve the desired liquidity in time periods, and in order to solve the model, goal programming has been used and in order to cover uncertainty conditions, interval programming has been used. Finally, the model was solved using GAMS software and CPLEX solver, and the results, in addition to proposing appropriate financial and physical flows in the supply chain, have proposed an appropriate factoring financing program to small and medium-sized manufacturing enterprises to provide the necessary liquidity in each period and increase profitability

Electronic Business Development Strategies in the Context of Facilitating and Improving Business Environment

E-business as one of the enablers of the economy and a subset of information technology has grown substantially in the past decade. Today’s global markets is changing and transforming from industrial market to a science and technology one. In other words, today's business environment has reshaped from physical to electronic and has transformed traditional and offline markets. Successful investors have accepted transformation of traditional business to e-business so that policies of commercial enterprises in adoption and deployment of e-business are effective and efficient in order to enter international markets and attract new customers. The importance of e-business environment and high degree of its acceptance by people and businesses, have led to feel the importance of planning and development of e-business strategies and frameworks. This study, presents the results of a project administered by Ministry of Information and Communications Technology of Iran, named “Electronic business development strategies in the context of facilitating and improving the business environment “.The purpose of this project is to extract and codify the business development strategies in the field of communications and technology, which has been designed and implemented in four phases.The fourth and final phase of this project, presents a new model based on e-readiness frameworks and was confirmed by using Smart PLS software. Finally, the e-business development strategies have extracted and classified based on confirmed model and SWOT analysis

Credit Status Assessment of Bank Loan Applicants Using CBR Method

Credit risk assessment is one of the key issues for banks and financial institutions and various models have been developed for this. This study uses Case Based reasoning (CBR) Model and considers a database of bank credit customers to assess the credit risk of bank applicants. For this, 9 criteria were selected based on the experts' opinion and were weighted using the Fuzzy Analytical Hierarchy Process (FAHP). Return check, housing situation and income level are the most important criteria for credit risk assessment of the bank applicants. Then, using the TOPSIS Technique, we could evaluates the similarity of the new item with actual past cases or evaluate the new applicant with the ideal option, and uses a case-based reasoning model to predict the likelihood of default or non-default applicants. Survey research was applied for this study and the research community was the records of previous bank applicants between 1390-94 years. This research is an applied and descriptive and descriptive study. The results show that the accuracy of the CBR model is higher than other validation and ranking methods of bank customers. The use of the CBR model in order to authenticate customers has obtained results far better than the performance of the credit sector experts, which led to the judgment of default or non-default of customers, indicating the high performance of the model used in comparison to the model used by bank and validation experts. CBR leads to the design an expert, specialized and intelligent system which addition to storing data in a database, stores models and templates for use