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.
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Proceedings Article•
22 Mar 2007TL;DR: In this paper, the concept of fuzzy weight aggregation was applied to performance aggregation, and an illustrative example was also applied to demonstrate the effectiveness of proposed procedure and the results showed that the proposed procedure is effective.
Abstract: As for the performance comparison, we can compare the difference between the actual performance and ideal performance with simultaneously taking all criteria into consideration. Hence, the practitionerw will meet a problem of MCDM. Besides, the importance of each criterion may have different priority and it should be taken into analysis. In this study, we will apply the concept of fuzzy weight aggregation into performance aggregation. An illustrative example will be also applied to demonstrate the effectiveness of proposed procedure.
1 citations
Cites methods from "Using AHP for resource allocation p..."
...Next, the membership degree μij for each point with respect to the ideal point can be computed via the Equ (1): { }iji ij ij X X max =μ (1) Step2....
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...Then, the close degree for each project with respect to the ideal point Pki can be computed as Equ (5): { }kik ki ki Y YP max = (5) Step6....
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...The average weight of i-th criterion (wi) can be computed as Equ (4) by using ei....
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...That is, we must prove 0f ki k P AP ∂ ∂ and the proof procedure will be listed in Equ (7)....
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...Hence, we can apply the full deviation of APk with respect to iw into analyzing the affection of APk derived from the weight values and it is denoted as Equ(8)....
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01 Jan 2000
TL;DR: In this paper, the authors formulate the problem of a service-oriented public sector entity to allocate limited resources to diAerent activities while keeping conflicting objectives in mind, and develop a two-stage algorithm to generate and evaluate DMUs.
Abstract: This paper concerns the problem of a service-oriented public sector entity to allocate limited resources to diAerent activities while keeping conflicting objectives in mind. The Multi-objective Resource Allocation Problem (MRAP) is to select activities to be performed. The authors formulate the problem as a multi-objective 0‐1 linear problem. The authors implement Data Envelopment Analysis (DEA) with the Banker, Charnes and Cooper’s (BCC) model to measure the Decision Making Unit’s (DMU) eAciency. In this study, the production function is a mathematical statement relating the technological relationship between the objectives and resources of MRAP. Each DMU presents a technological relationship, i.e. DMU presents a relationship between resources and objectives. This relationship gives information about the use of resources and satisfactoriness of objectives. The inputs and outputs, respectively, outline resources and objectives. The production possibility set represents feasible solutions for MRAP. Moreover, due to the multiple objectives of problems, the method derives a solution set instead of an optimal solution in single objective ones. This solution set, a well-known eAcient solutions set, forms the decision set of problems. Each DMU results from an alternative, a combination of activities. The production possibility set presents all the candidates of DMU. The set of alternatives resulting in eAcient DMUs is eAcient solutions of MRAP. The authors developed a two-stage algorithm to generate and evaluate DMUs. The first stage generates a DMU with the maximum of the distance function. The second stage is then used to evaluate the eAciency of the generated DMU. ” 2000 Elsevier Science B.V. All rights reserved.
1 citations
Proceedings Article•
30 Apr 2017TL;DR: This work proposes three scoring methods that convert any attribute into a numerical representation that can be used for comparison and means that managers can select any attributes of importance to allow their portfolio to be prioritised and have the resource allocated appropriately to the projects that offer the greatest promise.
Abstract: To achieve competitive advantage, many companies need to engage and invest in Research and Development. For this investment to be effective, resources need to be allocated appropriately across all projects. However, when the portfolio of the company is diverse or large, this assignment can be challenging. Portfolio Management has been created as a method for companies to effectively manage new, existing and potential projects. Yet, these methods can introduce bias and subjectivity without being flexible to the pieces of information, or attributes that are important to the company. This work adds to the field by proposing three scoring methods that convert any attribute into a numerical representation that can then be used for comparison. For managers, it means that they can select any attributes of importance to them to allow their portfolio to be prioritised and have the resource allocated appropriately to the projects that offer the greatest promise. KeywordsPortfolio Management; New Product Development; Scoring; Prioritisation
1 citations
Cites background from "Using AHP for resource allocation p..."
...Process [17]–[19], which uses a four point scale around a midpoint towards each attribute being compared....
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01 Jun 2011
1 citations
01 Jan 2019
TL;DR: This research overcomes a number of drawbacks, including longer development time and increased cost, both of which it overcomes by considering the system as a whole and generating an executable model to permit testing.
Abstract: Existing vehicle electronics design is largely divided by feature, with integration taking place at a late stage. This leads to a number of drawbacks, including longer development time and increased cost, both of which this research overcomes by considering the system as a whole and, in particular, generating an executable model to permit testing. To generate such a model, a number of inputs needed to be made available. These include a structural description of the vehicle electronics, functional descriptions of both the electronic control units and the communications buses, the application code that implements the feature and software patterns to implement the low-level interfaces to sensors and actuators. [Continues.]
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