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Multicriteria models for fair resource allocation

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Resource allocation problems are concerned with the allocation of limited resources among competing activities so as to achieve the best performances. However, in systems which serve many users there is a need to respect some fairness rules while looking for the overall efficiency. The so-called Max-Min Fairness is widely used to meet these goals. However, allocating the resource to optimize the worst performance may cause dramatic worsening of the overall system efficiency. Therefore, several other fair allocation schemes are being considered and analyzed. In this paper we show how the concepts of multiple criteria equitable optimization can effectively be used to generate various fair and efficient allocation schemes. First, we demonstrate how the scalar inequality measures can be consistently used in bicriteria models to search for fair and efficient allocations. Further, two alternative multiple criteria models equivalent to equitable optimization are introduced, thus allowing to generate a larger variety of fair and efficient resource allocation schemes.
Rocznik
Strony
303--332
Opis fizyczny
Bibliogr. 46 poz., wykr.
Twórcy
autor
  • Warsaw University of Technology, Institute of Control and Computation Engineering, Nowowiejska 15/19, 00-665 Warsaw, Poland, W.Ogryczak@ia.pw.edu.pl
Bibliografia
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  • KLEIN, R.S., LUSS, H. and ROTHBLUM U.G. (1993) Minimax Resource Allocation Problems with Resource-Substitutions Represented by Graphs. Operations Research 41, 959-971.
  • KOSTREVA, M.M. and OGRYCZAK, W. (1999) Linear Optimization with Multiple Equitable Criteria. RAIRO Rech. Oper. 33, 275-297.
  • KOSTREVA, M.M., OGRYCZAK, W. and WIERZBICKI, A. (2004) Equitable Aggregations and Multiple Criteria Analysis. European Journal of Operational Research 158, 362-367, 2004.
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  • MARSH, M.T. and SCHILLING D.A. (1994) Equity Measurement in Facility Location Analysis: A Review and Framework. European J. of Operational Research 74, 1-17.
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  • OGRYCZAK, W. (1997) Linear and Discrete Optimization with Multiple Criteria: Preference Models and Applications to Decision Support (in Polish). Warsaw Univ. Press, Warsaw.
  • OGRYCZAK, W. (2000) Inequality Measures and Equitable Approaches to Location Problems. European J. of Operational Research 122, 374-391.
  • OGRYCZAK, W. (2001) Comments on Properties of the Minimax Solutions in Goal Programming. European J. of Operational Research 132, 17-21.
  • OGRYCZAK, W. (2002) Multiple Criteria Optimization and Decisions under Risk. Control and Cybernetics 31, 975-1003.
  • OGRYCZAK, W., MILEWSKI, M. and WIERZBICKI, A. (2006) On Fair and Efficient Bandwidth Allocation by the Multiple Target Approach. 2006 NGI - Next Generation Internet Design and Engineering, IEEE, 48-55.
  • OGRYCZAK, W. and RUSZCZYNSKI, A. (1999) From Stochastic Dominance to Mean-Risk Models: Semideviations as Risk Measures. European J. of Operational Research 116, 33-50.
  • OGRYCZAK, W. and RUSZCZYŃSKI, A. (2002) Dual Stochastic Dominance and Related Mean-Risk Models. SIAM J. on Optimization 13, 60-78.
  • OGRYCZAK, W. and ŚLIWIŃSKI, T. (2002) On Equitable Approaches to Resource Allocation Problems: the Conditional Minimax Solution. J. of Telecommunications and Information Technology 3, 40-48.
  • OGRYCZAK, W. and ŚLIWIŃSKI, T. (2003) On Solving Linear Programs with the Ordered Weighted Averaging Objective. European J. of Operational Research, 148, 80-91.
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  • OGRYCZAK, W., ŚLIWIŃSKI, T. and WIERZBICKI, A. (2003) Fair Resource Allocation Schemes and Network Dimensioning Problems. J. of Telecommunications and Information Technology 3, 34-42.
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  • YOUNG, H.P. (1994) Equity in Theory and Practice. Princeton Univ. Press, Princeton.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0017-0041
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