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Congestion: Its Identification and Management with DEA

In: Handbook on Data Envelopment Analysis

Author

Listed:
  • William W. Cooper

    (University of Texas at Austin)

  • Honghui Deng

    (University of Nevada)

  • Lawrence M. Seiford

    (University of Michigan at Ann Arbor)

  • Joe Zhu

    (Worcester Polytechnic Institute)

Abstract

Congestion is a term that is applicable in a variety of disciplines which range from medical science to traffic engineering. It has also many uses in practical everyday life. This brings with it a certain looseness in usage. We therefore expand (and refine) our discussion of congestion with reference to its use in economics where we have access to a precise meaning which we can develop in this chapter. This chapter covers the standard approaches used for treating congestion in data envelopment analysis.

Suggested Citation

  • William W. Cooper & Honghui Deng & Lawrence M. Seiford & Joe Zhu, 2011. "Congestion: Its Identification and Management with DEA," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 173-193, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-6151-8_7
    DOI: 10.1007/978-1-4419-6151-8_7
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    Cited by:

    1. Mehdiloozad, Mahmood & Zhu, Joe & Sahoo, Biresh K., 2018. "Identification of congestion in data envelopment analysis under the occurrence of multiple projections: A reliable method capable of dealing with negative data," European Journal of Operational Research, Elsevier, vol. 265(2), pages 644-654.

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