Resource allocation problem based on the DEA model

Ito, Ryuzo; Namatame, Takashi; Yamaguchi, Toshimitsu

doi:10.1016/s0453-4514(99)80012-x

Cited by 4 publications

(7 citation statements)

References 13 publications

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“…Athanassopoulos et al [6] applied maximum and minimum bounds on inputs that had to be satis ed after reallocation for each DMU. Ito et al [7], using the DEA-BCC model, reallocated the management resources to produce the maximum outputs in the production possibility set. Yan et al [8] developed an inverse generalized DEA model and they then presented the application of the extended model to solve the resource reallocation problem.…”

Section: Related Literaturementioning

confidence: 99%

“…We are able to add the fairness goal to the conventional resource allocation model by the α-fairness measure, which quanti es fairness based on the utility theory. Before moving on, we rst give the proposed bi-criteria model (7). The detailed explanations are as follows: where W α (u) is the α-fairness.…”

Section: New Integrated Modelmentioning

confidence: 99%

“…The meanings of the other constraints are the same as those in model (3). Now we discuss two important elements of model (7) in the rest of this section: the utility function in (7.4) and the ef ciency measure in (7.2).…”

Section: New Integrated Modelmentioning

confidence: 99%

“…Thus choosing a suitable utility function is of great concern. In model (7), we give a general form of a utility function as (7.4).…”

Section: Utility Functionmentioning

confidence: 99%

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Integration of α-fairness with DEA based resource allocation model

Bi¹,

Wang²,

Ding³

2014

J. of Syst. Eng. Electron.

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How to allocate a resource ef ciently and fairly attracts the attention of both researchers and practitioners. Data envelopment analysis (DEA) has been brought to bear on its solution. The existing literature applies Gini coef cient to measure the fairness in the resource allocation process. However, the Gini coef cient is inapplicable in many applications. This paper proposes a novel centralized resource allocation model based on DEA that considers both the ef ciency and the fairness. This paper adopts a notion of fairness, namely α-fairness that is well studied in welfare economics and is of practical signi cance. The new model integrates α-fairness with DEA to support resource allocation decisions. It aids decision makers in making a trade-off between the ef ciency and the fairness. An illustrative application is used to validate the proposed approach.

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Section: Related Literaturementioning

confidence: 99%

Section: New Integrated Modelmentioning

confidence: 99%

Section: New Integrated Modelmentioning

confidence: 99%

“…Thus choosing a suitable utility function is of great concern. In model (7), we give a general form of a utility function as (7.4).…”

Section: Utility Functionmentioning

confidence: 99%

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Integration of α-fairness with DEA based resource allocation model

Bi¹,

Wang²,

Ding³

2014

J. of Syst. Eng. Electron.

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“…Each model or algorithm is a sub model in our algorithm framework to solve the resource allocation problem. Here, the resource allocation problem with the plural DMUs can be treated as a selection problem [24] , and our classification is according to the returns to scale of DMUs. The production frontier is also based on the BCC model which considering the variable returns to scale.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Dea Approach for the Resource Allocation Problem based on Scale Economies Classification

Cui

2008

J Syst Sci Complex

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This paper is concerned with the resource allocation problem based on data envelopment analysis (DEA) which is generally found in practice such as in public services and in production process. In management context, the resource allocation has to achieve the effective-efficient-equality aim and tries to balance the different desires of two management layers: central manager and each sector. In mathematical programming context, to solve the resource allocation asks for introducing many optimization techniques such as multiple-objective programming and goal programming. We construct an algorithm framework by using comprehensive DEA tools including CCR, BCC models, inverse DEA model, the most compromising common weights analysis model, and extra resource allocation algorithm. Returns to scale characteristic is put major place for analyzing DMUs' scale economies and used to select DMU candidates before resource allocation. By combining extra resource allocation algorithm with scale economies target, we propose a resource allocation solution, which can achieve the effective-efficient-equality target and also provide information for future resource allocation. Many numerical examples are discussed in this paper, which also verify our work.Key words Common weights analysis (CWA), date envelopment analysis (DEA), decision making unit (DMU), efficiency score, inverse DEA model, multiple-objective linear programming (MOLP), resource allocation problem, returns to scale (RTS).

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