An evolutionary agent system for mathematical programming

  • Authors:

  • Abu S. S. M. Barkat Ullah;Ruhul Sarker;David Cornforth

  • Affiliations:

  • School of Information Technology and Electrical Engineering, University of New South Wales at the Australian Defence Force Academy, Canberra, Australia;School of Information Technology and Electrical Engineering, University of New South Wales at the Australian Defence Force Academy, Canberra, Australia;School of Information Technology and Electrical Engineering, University of New South Wales at the Australian Defence Force Academy, Canberra, Australia

  • Venue:
  • ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
  • Year:
  • 2007

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Abstract

During the last decade, both evolutionary computation and multi-agent systems have been used for solving decision and optimization problems. This paper proposes a new evolutionary agent system by incorporating evolutionary process into agent concepts for solving mathematical programming models. Each of the agents represents a candidate solution of the problem, and able to sense and act on the society. The fitness of the agent improves through co-evolutionary adaptation of society with the individual learning of the agents. The performance of the proposed algorithm is tested on five new benchmark problems along with existing 13 well-known problems, and the experimental results show convincing performance.