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Privacy Preserving Decentralized Method for Computing a Pareto-Optimal Solution

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Distributed Computing – IWDC 2005 (IWDC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3741))

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Abstract

Distributed methodologies to find pareto-optimal frontier with concern to privacy, of objectives and constraints, of parties is of interest in scenarios like negotiations. Adaptation of lagrangian method to solve distributed weighting method for both strictly concave and not strictly concave (e.g. linear) value functions is proposed for a maximization problem.

The work is partly supported by the AICTE project ISISAMB.

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References

  1. Miettinen, K.M.: Nonlinear Multiobjective Optimization. Kluwer Academic Publishers, Dordrecht (1999)

    MATH  Google Scholar 

  2. Heiskanen, P.: Decentralized method for computing pareto solutions in multiparty negotiations. European Journal of Operational Research 117, 578–590 (1999)

    Article  MATH  Google Scholar 

  3. Goldreich, O.: Secure multi-party computation (working draft) Version 1.1 (1998), http://www.wisdom.weizmann.ac.il/~oded/pp.html (accessed on Febuary 10, 2004)

  4. Huang, M.A., Teng, S.: Secure and verifiable schemes for election and general distributed computing problems. In: Seventh Annual ACM Symposium on Principles of Distributed Computing, pp. 182–196. ACM Press, New York (1988)

    Chapter  Google Scholar 

  5. Bertsekas, D.P., Tsitsiklis, J.N.: Parallel and Distributed Computation, 2nd edn. Prentice–Hall International Editions, Englewood Cliffs (1989)

    MATH  Google Scholar 

  6. Sehgal, S.K., Pal, A.K.: A hybrid method to find pareto-optimal extreme points for linear optimization in multi-party negotiations. In: Thirteenth Workshop on Information Technology and Systems (WITS), Seattle, Washington, USA (2003)

    Google Scholar 

  7. Sehgal, S.K., Pal, A.K.: Finding pareto-optimal set of distributed vectors for negotiation with minimum disclosure. In: Sen, A., Das, N., Das, S.K., Sinha, B.P. (eds.) IWDC 2004. LNCS, vol. 3326, pp. 144–149. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

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Authors and Affiliations

  1. Indian Institute of Management Calcutta, Kolkata, India

    Satish K. Sehgal & Asim K. Pal

Authors
  1. Satish K. Sehgal
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  2. Asim K. Pal
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India

    Ajit Pal

  2. Department of Computer Science, University of Illinois at Chicago, 60607, Chicago, Illinois

    Ajay D. Kshemkalyani

  3. Computer Science and Engineering Department, Indian Institute of Technology, 721 302, Kharagpur, WB, India

    Rajeev Kumar

  4. Department of Computer Science and Engineering, Indian Institute of Technology, 721 302, Kharagpur, India

    Arobinda Gupta

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Sehgal, S.K., Pal, A.K. (2005). Privacy Preserving Decentralized Method for Computing a Pareto-Optimal Solution. In: Pal, A., Kshemkalyani, A.D., Kumar, R., Gupta, A. (eds) Distributed Computing – IWDC 2005. IWDC 2005. Lecture Notes in Computer Science, vol 3741. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11603771_66

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  • DOI: https://doi.org/10.1007/11603771_66

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30959-8

  • Online ISBN: 978-3-540-32428-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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