Distributed multiprocessor scheduling with decomposed optimization criterion

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "F. Seredyski and J. Koronacki and C. Z. Janikow",
  title =        "Distributed multiprocessor scheduling with decomposed
                 optimization criterion",
  journal =      "Future Generation Computer Systems",
  volume =       "17",
  pages =        "387--396",
  year =         "2001",
  number =       "4",
  keywords =     "genetic algorithms, genetic programming,
                 Multiprocessor scheduling, Multi-agent systems,
                 Decomposition of optimization criterion",
  URL =          "http://www.sciencedirect.com/science/article/B6V06-4234BR7-6/1/9ac251ca310222336e096ca3ecf27e22",
  DOI =          "doi:10.1016/S0167-739X(99)00119-3",
  abstract =     "n this paper, a new approach to scheduling of parallel
                 and distributed algorithms for multiprocessor systems
                 is proposed. Its main innovation lies in evolving a
                 decomposition of the global optimization criteria. For
                 this purpose, agents {"}local decision making units{"}
                 are associated with individual tasks of the program
                 graph. Thus, the program can be interpreted as a
                 multi-agent system. A game-theoretic model of
                 interaction between agents is applied. Agents take part
                 in an iterated game to find directions of migration in
                 the system graph, with the objective of minimizing the
                 total execution time of the program in a given
                 multiprocessor topology. Competitive coevolutionary
                 genetic algorithm, termed loosely coupled genetic
                 algorithm, is used to implement the multi-agent system.
                 The scheduling algorithm works with a global
                 optimization function, what limits its efficiency. To
                 make the algorithm truly distributed, decomposition of
                 the global optimization criterion into local criteria
                 is proposed. This decomposition is evolved with genetic
                 programming. Results of successive experimental study
                 of the proposed algorithm are presented.",

Genetic Programming entries for F Seredyski Jacek Koronacki Cezary Z Janikow