782 resultados para constrained fuzzy analytic hierarchy process (AHP)
Resumo:
The Intensive Care Unit (ICU) being one of those vital areas of a hospital providing clinical care, the quality of service rendered must be monitored and measured quantitatively. It is, therefore, essential to know the performance of an ICU, in order to identify any deficits and enable the service providers to improve the quality of service. Although there have been many attempts to do this with the help of illness severity scoring systems, the relative lack of success using these methods has led to the search for a form of measurement, which would encompass all the different aspects of an ICU in a holistic manner. The Analytic Hierarchy Process (AHP), a multiple-attribute, decision-making technique is utilised in this study to evolve a system to measure the performance of ICU services reliably. This tool has been applied to a surgical ICU in Barbados; we recommend AHP as a valuable tool to quantify the performance of an ICU. Copyright © 2004 Inderscience Enterprises Ltd.
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The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests efficient design and operation philosophy, construction methodology and logical insurance plans. The risk-based model uses Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.
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Conventional project management techniques are not always sufficient for ensuring time, cost and quality achievement of large-scale construction projects due to complexity in planning and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in Government policies and regulations, unforeseen inflation) under-estimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk numagement throughout project life cycle. However, the effectiveness of risk management depends on the technique in which the effects of risk factors are analysed and! or quantified. This study proposes Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique as a tool for risk analysis because it can handle subjective as well as objective factors in decision model that are conflicting in nature. This provides a decision support system (DSS) to project managenumt for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and competitive business environment. The whole methodology is explained through a case study of a cross-country petroleum pipeline project in India and its effectiveness in project1nana.gement is demonstrated.
Resumo:
Conventional project management techniques are not always sufficient to ensure time, cost and quality achievement of large-scale construction projects due to complexity in planning, design and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in government policies and regulations, unforeseen inflation, underestimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk management throughout the project's life cycle. However, the effectiveness of risk management depends on the technique through which the effects of risk factors are analysed/quantified. This study proposes the Analytic Hierarchy Process (AHP), a multiple attribute decision making technique, as a tool for risk analysis because it can handle subjective as well as objective factors in a decision model that are conflicting in nature. This provides a decision support system (DSS) to project management for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and a competitive business environment. The whole methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.
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Petroleum pipelines are the nervous system of the oil industry, as this transports crude oil from sources to refineries and petroleum products from refineries to demand points. Therefore, the efficient operation of these pipelines determines the effectiveness of the entire business. Pipeline route selection plays a major role when designing an effective pipeline system, as the health of the pipeline depends on its terrain. The present practice of route selection for petroleum pipelines is governed by factors such as the shortest distance, constructability, minimal effects on the environment, and approachability. Although this reduces capital expenditure, it often proves to be uneconomical when life cycle costing is considered. This study presents a route selection model with the application of an Analytic Hierarchy Process (AHP), a multiple attribute decision making technique. AHP considers all the above factors along with the operability and maintainability factors interactively. This system has been demonstrated here through a case study of pipeline route selection, from an Indian perspective. A cost-benefit comparison of the shortest route (conventionally selected) and optimal route establishes the effectiveness of the model.
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This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional costbased approach.
An integrated multiple criteria decision making approach for resource allocation in higher education
Resumo:
Resource allocation is one of the major decision problems arising in higher education. Resources must be allocated optimally in such a way that the performance of universities can be improved. This paper applies an integrated multiple criteria decision making approach to the resource allocation problem. In the approach, the Analytic Hierarchy Process (AHP) is first used to determine the priority or relative importance of proposed projects with respect to the goals of the universities. Then, the Goal Programming (GP) model incorporating the constraints of AHP priority, system, and resource is formulated for selecting the best set of projects without exceeding the limited available resources. The projects include 'hardware' (tangible university's infrastructures), and 'software' (intangible effects that can be beneficial to the university, its members, and its students). In this paper, two commercial packages are used: Expert Choice for determining the AHP priority ranking of the projects, and LINDO for solving the GP model. Copyright © 2007 Inderscience Enterprises Ltd.
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This paper explores the use of the optimization procedures in SAS/OR software with application to the contemporary logistics distribution network design using an integrated multiple criteria decision making approach. Unlike the traditional optimization techniques, the proposed approach, combining analytic hierarchy process (AHP) and goal programming (GP), considers both quantitative and qualitative factors. In the integrated approach, AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, a GP model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. To facilitate the use of integrated multiple criteria decision making approach by SAS users, an ORMCDM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear programming models based on the selected GP model. An example is given to illustrate how one could use the code to design the logistics distribution network.
Resumo:
Spare parts warehousing decision-making plays an important role in today's manufacturing industry as it derives an optimum inventory policy for the organizations. Previous research on spare parts warehousing decision-making did not deal with the problem holistically considering all the subjective and objective criteria of operational and strategic needs of the manufacturing companies in the process industry. This study reviews current relevant literature and develops a conceptual framework (an integrated group decision support system) for selecting the most effective warehousing option for the process industry using the analytic hierarchy process (AHP). The framework has been applied to a multinational cement manufacturing company in the UK. Three site visits, eight formal interviews, and several discussions have been undertaken with personnel of the organization, many of which have more than 20 years of experience, in order to apply the proposed decision support system (DSS). Subsequently, the DSS has been validated through a questionnaire survey in order to establish its usefulness, effectiveness for warehousing decision-making, and the possibility of adoption. The proposed DSS is an integrated framework for selecting the best warehousing option for business excellence in any manufacturing organization.
Resumo:
The cross-country petroleum pipelines are environmentally sensitive because they traverse through varied terrain covering crop fields, forests, rivers, populated areas, desert, hills and offshore. Any malfunction of these pipelines may cause devastating effect on the environment. Hence, the pipeline operators plan and design pipelines projects with sufficient consideration of environment and social aspects along with the technological alternatives. Traditionally, in project appraisal, optimum technical alternative is selected using financial analysis. Impact assessments (IA) are then carried out to justify the selection and subsequent statutory approval. However, the IAs often suggest alternative sites and/or alternate technology and implementation methodology, resulting in revision of entire technical and financial analysis. This study addresses the above issues by developing an integrated framework for project feasibility analysis with the application of analytic hierarchy process (AHP), a multiple attribute decision-making technique. The model considers technical analysis (TA), socioeconomic IA (SEIA) and environmental IA (EIA) in an integrated framework to select the best project from a few alternative feasible projects. Subsequent financial analysis then justifies the selection. The entire methodology has been explained here through a case application on cross-country petroleum pipeline project in India.
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A cross-country pipeline construction project is exposed to an uncertain environment due to its enormous size (physical, manpower requirement and financial value), complexity in design technology and involvement of external factors. These uncertainties can lead to several changes in project scope during the process of project execution. Unless the changes are properly controlled, the time, cost and quality goals of the project may never be achieved. A methodology is proposed for project control through risk analysis, contingency allocation and hierarchical planning models. Risk analysis is carried out through the analytic hierarchy process (AHP) due to the subjective nature of risks in construction projects. The results of risk analysis are used to determine the logical contingency for project control with the application of probability theory. Ultimate project control is carried out by hierarchical planning model which enables decision makers to take vital decisions during the changing environment of the construction period. Goal programming (GP), a multiple criteria decision-making technique, is proposed for model formulation because of its flexibility and priority-base structure. The project is planned hierarchically in three levels—project, work package and activity. GP is applied separately at each level. Decision variables of each model are different planning parameters of the project. In this study, models are formulated from the owner's perspective and its effectiveness in project control is demonstrated.
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In the contemporary customer-driven supply chain, maximization of customer service plays an equally important role as minimization of costs for a company to retain and increase its competitiveness. This article develops a multiple-criteria optimization approach, combining the analytic hierarchy process (AHP) and an integer linear programming (ILP) model, to aid the design of an optimal logistics distribution network. The proposed approach outperforms traditional cost-based optimization techniques because it considers both quantitative and qualitative factors and also aims at maximizing the benefits of deliverer and customers. In the approach, the AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to some critical customer-oriented criteria. The results of AHP prioritization are utilized as the input of the ILP model, the objective of which is to select the best warehouses at the lowest possible cost. In this article, two commercial packages are used: including Expert Choice and LINDO.
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The aim of the paper is to present a new global optimization method for determining all the optima of the Least Squares Method (LSM) problem of pairwise comparison matrices. Such matrices are used, e.g., in the Analytic Hierarchy Process (AHP). Unlike some other distance minimizing methods, LSM is usually hard to solve because of the corresponding nonlinear and non-convex objective function. It is found that the optimization problem can be reduced to solve a system of polynomial equations. Homotopy method is applied which is an efficient technique for solving nonlinear systems. The paper ends by two numerical example having multiple global and local minima.
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Bus stops are key links in the journeys of transit patrons with disabilities. Inaccessible bus stops prevent people with disabilities from using fixed-route bus services, thus limiting their mobility. The Americans with Disabilities Act (ADA) of 1990 prescribes the minimum requirements for bus stop accessibility by riders with disabilities. Due to limited budgets, transit agencies can only select a limited number of bus stop locations for ADA improvements annually. These locations should preferably be selected such that they maximize the overall benefits to patrons with disabilities. In addition, transit agencies may also choose to implement the universal design paradigm, which involves higher design standards than current ADA requirements and can provide amenities that are useful for all riders, like shelters and lighting. Many factors can affect the decision to improve a bus stop, including rider-based aspects like the number of riders with disabilities, total ridership, customer complaints, accidents, deployment costs, as well as locational aspects like the location of employment centers, schools, shopping areas, and so on. These interlacing factors make it difficult to identify optimum improvement locations without the aid of an optimization model. This dissertation proposes two integer programming models to help identify a priority list of bus stops for accessibility improvements. The first is a binary integer programming model designed to identify bus stops that need improvements to meet the minimum ADA requirements. The second involves a multi-objective nonlinear mixed integer programming model that attempts to achieve an optimal compromise among the two accessibility design standards. Geographic Information System (GIS) techniques were used extensively to both prepare the model input and examine the model output. An analytic hierarchy process (AHP) was applied to combine all of the factors affecting the benefits to patrons with disabilities. An extensive sensitivity analysis was performed to assess the reasonableness of the model outputs in response to changes in model constraints. Based on a case study using data from Broward County Transit (BCT) in Florida, the models were found to produce a list of bus stops that upon close examination were determined to be highly logical. Compared to traditional approaches using staff experience, requests from elected officials, customer complaints, etc., these optimization models offer a more objective and efficient platform on which to make bus stop improvement suggestions.
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Informação Geográfica (SIG) ao estudo das energias renováveis, tendo como caso avaliar o potencial solar na ilha de São Vicente do arquipélago de Cabo Verde. A energia do sol é a principal fonte de energia renovável, e está disponível em quase todas as regiões do planeta. Quantificar o potencial energético solar de um lugar ou região é indispensável, para avaliar as potencialidades de produção de energia fotovoltaica. Outro fator importante prende-se com ordenamento territorial associado à exploração desses recursos energéticos, pelo que devem ser avaliadas as condições técnicas, ambientais e económicas, quando se pretende instalar parques para a produção de energia fotovoltaica. Assim, neste trabalho foram aplicadas as ferramentas SIG, para quantificar a radiação solar mensal e anual da ilha de São Vicente, arquipélago de Cabo Verde, através do modelo Solar Analyst. Numa segunda fase, aplicou-se a técnica de análise multicritério em combinação com os SIGs para definir as áreas mais favoráveis para a instalação de parques de produção de energia elétrica a partir da energia solar. Para o cálculo da radiação solar na ilha de São de Vicente, utilizou-se o modelo digital de terreno (MDT) e a latitude da ilha como parâmetros de entrada ao modelo. Para a análise multicritério definiram-se um conjunto de critérios que devem ser considerados na implementação de parques solares, nomeadamente, a disponibilidade de radiação solar existente na área, a distância à rede de transporte de energia elétrica e à rede viária, o declive do terreno, o uso e ocupação do solo e a proximidade às linhas de água. Para auxiliar na atribuição dos pesos aos critérios utilizados na análise aplicou-se a método Analytic Hierarchy Process (AHP). As áreas resultantes do processo da análise multicritério, foram confrontadas com a Carta de Condicionantes do esquema regional de ordenamento da ilha de São Vicente, aferindo a conformidade das propostas e reajustes subsequentes, de modo a obter os resultados finais.