Using AHP for resource allocation problems
TL;DR: AHP has been used for solving multi-criteria resource allocation problems by converting them into equivalent single objective, maximization-type LP problems as mentioned in this paper, and at least two approaches can be identified for such applications.
About: This article is published in European Journal of Operational Research.The article was published on 1995-01-19. It has received 125 citations till now. The article focuses on the topics: Preference elicitation & Resource allocation.
Citations
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30 Nov 2018
TL;DR: In this paper, a QFD optimization methodology is formulated with suitable illustrations and tried to find a best method of product design, which will be helpful to design such product having good quality with affordable price.
Abstract: Every customer wants to purchase the best quality product but the price factor is only the reason due to which most of customers compromise with quality. The main purpose of our study is to find a best suitable method which will be helpful to design such product having good quality with affordable price. Quality Function Deployment (QFD) is the most powerful method for analyzing the customer demands and selection of most important or valuable voice which has to be corrected or modified. The integrated approach of QFD and Optimization techniques (i.e. AHP, TOPSIS, PROMETHEE, etc.) can be used to analyze the product quality manufacturing industry. A QFD optimization methodology is formulated in this study with suitable illustrations and tried to find a best method of product design. Keywords: Quality Function Deployment, PROMETHEE, AHP, TOPSIS, House of Quality.
TL;DR: Weight effect for different categories of a qualitative response significantly exists in L/F manufacturing process and including such weight effect into the L/f manufacturing analysis can achieve the parameter optimization and enhance their quality improvemen...
Abstract: Purpose – No methodology has been directly proposed to address the parameter optimization problem with weight effect on the categorical response. The aim of this paper is to propose a suitable procedure to address such a problem.Design/methodology/approach – The computation of aggregation weight and neural network modeling technique were employed into forming the core architecture of the proposed approach. The consistency and difference of the weight effect between several experts or professionals can be included into the weight computation. The backpropagation neural network model is chosen to model the non‐linear relationship among the control factors, the probability, and the accumulated probability of categories for a qualitative response.Findings – Weight effect for different categories of a qualitative response significantly exists in L/F manufacturing process. Including such weight effect into the L/F manufacturing analysis can achieve the parameter optimization and enhance their quality improvemen...
TL;DR: A general framework methodology for consistently allocating resources is described that is concerned with risk perception and technical risk evaluation and not political obfuscation.
Abstract: Governmental agencies, such as the Department of Homeland Security in the United States, are required to distribute resources to different governmental units and locations in response to risk associated with various natural and man-made threats. There are always significant political arguments about how to distribute, and who should receive, significant resources in reaction to threat. This paper describes a general framework methodology for consistently allocating resources. The end result is a model that is concerned with risk perception and technical risk evaluation and not political obfuscation.
31 May 2016
TL;DR: A well-established technique is introduced in this chapter which can be used to identify major hazards and evaluate both qualitative and quantitative risk data, and information associated with railway operation efficiently and effectively in an acceptable way in various environments.
Abstract: Railway safety is a very complicated subject, which is determined by numerous aspects. Many of qualitative and quantitative railway safety and risk analysis techniques and methods are used in the industry. But, however, the railway industry faces problems and challenges on how to apply these techniques and methods effectively and efficiently, particularly in the circumstances where the risk data are incomplete or there is a high level of uncertainty involved in the risk data. This chapter approaches these subjects to discuss the problems and challenges of railway safety and risk analysis methods in dealing with uncertainties, and those growing needs of the industry. A well-established technique is also introduced in this chapter which can be used to identify major hazards and evaluate both qualitative and quantitative risk data, and information associated with railway operation efficiently and effectively in an acceptable way in various environments.
References
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01 Jan 1985
TL;DR: Analytic Hierarchy Process (AHP) as mentioned in this paper is a systematic procedure for representing the elements of any problem hierarchically, which organizes the basic rationality by breaking down a problem into its smaller constituent parts and then guides decision makers through a series of pairwise comparison judgments to express the relative strength or intensity of impact of the elements in the hierarchy.
Abstract: This chapter provides an overview of Analytic Hierarchy Process (AHP), which is a systematic procedure for representing the elements of any problem hierarchically. It organizes the basic rationality by breaking down a problem into its smaller constituent parts and then guides decision makers through a series of pair-wise comparison judgments to express the relative strength or intensity of impact of the elements in the hierarchy. These judgments are then translated to numbers. The AHP includes procedures and principles used to synthesize the many judgments to derive priorities among criteria and subsequently for alternative solutions. It is useful to note that the numbers thus obtained are ratio scale estimates and correspond to so-called hard numbers. Problem solving is a process of setting priorities in steps. One step decides on the most important elements of a problem, another on how best to repair, replace, test, and evaluate the elements, and another on how to implement the solution and measure performance.
16,547 citations
Book•
01 Jan 1976TL;DR: In this article, a confused decision maker, who wishes to make a reasonable and responsible choice among alternatives, can systematically probe his true feelings in order to make those critically important, vexing trade-offs between incommensurable objectives.
Abstract: Many of the complex problems faced by decision makers involve multiple conflicting objectives. This book describes how a confused decision maker, who wishes to make a reasonable and responsible choice among alternatives, can systematically probe his true feelings in order to make those critically important, vexing trade-offs between incommensurable objectives. The theory is illustrated by many real concrete examples taken from a host of disciplinary settings. The standard approach in decision theory or decision analysis specifies a simplified single objective like monetary return to maximise. By generalising from the single objective case to the multiple objective case, this book considerably widens the range of applicability of decision analysis.
8,895 citations
TL;DR: This paper presents a meta-modelling architecture suitable for multiobjective analysis of the decision-Making process and some of the strategies used in this process have been developed.
Abstract: Keywords: Decision-Making ; multiobjective analysis Reference Record created on 2005-06-20, modified on 2016-08-08
729 citations
TL;DR: In this article, an extension of the Analytic Hierarchy Process (AHP) for priority setting and resource allocation in the industrial R&D environment is explored, and an AHP modeling framework is developed, and is linked to a spreadsheet model to assist in the ranking of a large number of project alternatives.
Abstract: The research and development project selection decision is concerned with the allocation of resources to a set of proposals for scientific and engineering activities. The project selection and resource allocation process can be viewed as a multiple-criteria decision-making problem, within the context of the long-range and strategic planning process of the firm. The purpose of this paper is explore the applicability of an extension of the Analytic Hierarchy Process (AHP) for priority setting and resource allocation in the industrial R&D environment. In this paper, an AHP modeling framework for the R&D project selection decision is developed, and is linked to a spreadsheet model to assist in the ranking of a large number of project alternatives. Next, cost-benefit analysis and integer programming are used to assist in the resource allocation decision. The paper concludes with an evaluation of the suitability of this approach as an expert support system, and directions for future research and testing.
260 citations