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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01 Jan 2013
TL;DR: A Non-Linear Programming model is developed that calculates PCM element weights which maximizes the preferences of the DM as well as minimizes the inconsistency simultaneously, to address limitations of a PCM Framework for Large-Scale Decisions.
Abstract: A Pairwise Comparison Matrix (PCM) is used to compute for relative priorities of criteria or alternatives and are integral components of widely applied decision making tools: the Analytic Hierarchy Process (AHP) and its generalized form, the Analytic Network Process (ANP). However, a PCM suffers from several issues limiting its application to large-scale decision problems, specifically: (1) to the curse of dimensionality, that is, a large number of pairwise comparisons need to be elicited from a decision maker (DM), (2) inconsistent and (3) imprecise preferences maybe obtained due to the limited cognitive power of DMs. This dissertation proposes a PCM Framework for Large-Scale Decisions to address these limitations in three phases as follows.
The first phase proposes a binary integer program (BIP) to intelligently decompose a PCM into several mutually exclusive subsets using interdependence scores. As a result, the number of pairwise comparisons is reduced and the consistency of the PCM is improved. Since the subsets are disjoint, the most independent pivot element is identified to connect all subsets. This is done to derive the global weights of the elements from the original PCM. The proposed BIP is applied to both AHP and ANP methodologies. However, it is noted that the optimal number of subsets is provided subjectively by the DM and hence is subject to biases and judgement errors.
The second phase proposes a trade-off PCM decomposition methodology to decompose a PCM into a number of optimally identified subsets. A BIP is proposed to balance the: (1) time savings by reducing pairwise comparisons, the level of PCM inconsistency, and (2) the accuracy of the weights. The proposed methodology is applied to the AHP to demonstrate its advantages and is compared to established methodologies.
In the third phase, a beta distribution is proposed to generalize a wide variety of imprecise pairwise comparison distributions via a method of moments methodology. A Non-Linear Programming model is then developed that calculates PCM element weights which maximizes the preferences of the DM as well as minimizes the inconsistency simultaneously. Comparison experiments are conducted using datasets collected from literature to validate the proposed methodology.
3 citations
TL;DR: In this article, the authors present a project selection model which can enable reasonable resource allocation or determination of return rates by considering the core competencies for various investment options, based on both performance and ability to create a competitive advantage.
Abstract: In general, during decision making or negotiations, the investor and the investee may often have different opinions which result in conflicts. So, an objective standard to mitigate potential conflicts between investors and investees should be provided since it is highly important that rational decisions must be made when choosing investments from various options. However, the models currently used come with some problems for several reasons, for instance, the arbitrariness of the evaluator, the difficulty in understanding the relationships that exist among the various investment options (that is, alternatives to investments), inconsistency in priorities, and simply providing selection criteria without detailing the proportion of investment in each option or evaluating only a single investment option at a time without considering all options. Thus, in this research, we present a project selection model which can enable reasonable resource allocation or determination of return rates by considering the core competencies for various investment options. Here, core competency is based on both performance and ability to create a competitive advantage. For this, we deduce issue-specific structural power indicators and analyze quantitatively the resource allocation results based on negotiation power. Through this, it is possible to examine whether the proposed project selection model considers core competencies or not by comparing several project selection models currently used. Furthermore, the proposed model can be used on its own, or in combination with other methods. Consequently, the presented model can be used as a quantitative criterion for determining behavioral tactics, and also can be used to mitigate potential conflicts between the investor and the investee who are considering idiosyncratic investments, determined by an interplay between power and core competency.
3 citations
Cites methods from "Using AHP for resource allocation p..."
...Therefore, to resolve these problems, diverse combined methods have been proposed, for example, AHP (Analytic Hierarchy Process) and Integer Programming [10], AHP and linear programming [11], AHP and fuzzy [12], ANP (Analytic Network Process) and fuzzy [13], and multi-criterial analysis considering revenue [14]....
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TL;DR: The objective of this study is to propose a procedure about quality improvement based on artificial neural networks (ANNs) technique to deal with the parameter optimization of categorical response with different weight effect.
Abstract: Most quality improvement or quality analysis frequently focused on the issue of the quantitative quality response. The issue of addressing a qualitative or a categorical quality response is seldom mentioned. Until now, only a few studies addressed the parameter optimization for achieving quality improvement for a categorical response. However, the weight effect for different categorical level of response cannot be included into their analysis and it will limit the rationality and feasibility for the real applications. The objective of this study is to propose a procedure about quality improvement based on artificial neural networks (ANNs) technique to deal with the parameter optimization of categorical response with different weight effect. A case study involving a taping process from a lead frame (L/F) manufacturer in Taiwan’s science-based park demonstrates the rationality and feasibility of the proposed approach.
2 citations
TL;DR: Wang et al. as mentioned in this paper developed a two-phase knowledge extraction framework of liquid crystal display (LCD) to provide some useful knowledge for ordinary users and manufacturers, where the knowledge about important factors from ordinary users' viewpoints is extracted through an experiment.
Abstract: This study develops a two-phase knowledge extraction framework of liquid crystal display (LCD) to provide some useful knowledge for ordinary users and manufacturers. At the first phase, the knowledge about important factors from ordinary users' viewpoints is extracted through an experiment. At the second phase, a systematic method is developed to convert these important factors into related manufacturing techniques and materials from manufacturers' viewpoints. Finally, the two-phase knowledge extraction framework is demonstrated to illustrate the knowledge extraction process of LCD image quality.
2 citations
14 Aug 2009
TL;DR: Adopted fuzzy prioritization method uses fuzzy pair-wise comparison judgments rather than exact numerical values of the comparison ratios and transforms the initial fuzzy prioritizing problem into a non-linear program.
Abstract: Design scheme selection of railway freight car is a multiple criteria decision-making (MCDM) problem which includes fuzzy and uncertain factors. In order to obtain the optimal alternative in the decision-maker judgment, a model of combining fuzzy set theory with an analytic hierarchy process (AHP) is proposed. Using the triangular fuzzy numbers as a pair-wise comparison scale derives the priorities of different selection criteria and attributes. Adopted fuzzy prioritization method uses fuzzy pair-wise comparison judgments rather than exact numerical values of the comparison ratios and transforms the initial fuzzy prioritization problem into a non-linear program. As an example, three design schemes were compared and evaluated. The case study shows that the proposed method is a simple and effective tool for treating the uncertainty problems.
2 citations
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