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The Robust Weighted Multi-Objective Game

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  • Shaojian Qu
  • Ying Ji
  • Mark Goh

Abstract

This paper studies a class of multi-objective n-person non-zero sum games through a robust weighted approach where each player has more than one competing objective. This robust weighted multi-objective game model assumes that each player attaches a set of weights to its objectives instead of accessing accurate weights. Each player wishes to minimize its maximum weighted sum objective where the maximization is pointing to the set of weights. To address this new model, a new equilibrium concept-robust weighted Nash equilibrium is obtained. The existence of this new concept is proven on suitable assumptions about the multi-objective payoffs.

Suggested Citation

  • Shaojian Qu & Ying Ji & Mark Goh, 2015. "The Robust Weighted Multi-Objective Game," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-8, September.
    • Handle: RePEc:plo:pone00:0138970
    DOI: 10.1371/journal.pone.0138970
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    References listed on IDEAS

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    1. Jian Hu & Sanjay Mehrotra, 2012. "Robust and Stochastically Weighted Multiobjective Optimization Models and Reformulations," Operations Research, INFORMS, vol. 60(4), pages 936-953, August.
    2. Weber, Martin & Borcherding, Katrin, 1993. "Behavioral influences on weight judgments in multiattribute decision making," European Journal of Operational Research, Elsevier, vol. 67(1), pages 1-12, May.
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