A negotiation framework for linked combinatorial optimization problems

  • Authors:

  • Lei Duan;Mustafa K. Doğru;Ulaş Özen;J. Christopher Beck

  • Affiliations:

  • Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada;Alcatel-Lucent Bell Labs, 600 Mountain Avenue, Murray Hill, USA 07974;Alcatel-Lucent Bell Labs, Blanchardstown Industrial Park, Dublin 15, Ireland;Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada

  • Venue:
  • Autonomous Agents and Multi-Agent Systems
  • Year:
  • 2012

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Abstract

We tackle the challenge of applying automated negotiation to self-interested agents with local but linked combinatorial optimization problems. Using a distributed production scheduling problem, we propose two negotiation strategies for making concessions in a joint search space of agreements. In the first strategy, building on Lai and Sycara (Group Decis Negot 18(2):169---187, 2009), an agent concedes on local utility in order to achieve an agreement. In the second strategy, an agent concedes on the distance in an attribute space while maximizing its local utility. Lastly, we introduce a Pareto improvement phase to bring the final agreement closer to the Pareto frontier. Experimental results show that the new attribute-space negotiation strategy outperforms its utility-based counterpart on the quality of the agreements and the Pareto improvement phase is effective in approaching the Pareto frontier. This article presents the first study of applying automated negotiation to self-interested agents each with a local, but linked, combinatorial optimization problem.