Deterministic Learning Automata Solutions to the Equipartitioning Problem

  • Authors:
  • B. J. Oommen;D. C. Y. Ma

  • Affiliations:
  • -;-

  • Venue:
  • IEEE Transactions on Computers
  • Year:
  • 1988

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Abstract

Three deterministic learning automata solutions to the problem of equipartitioning are presented. Although the first two are epsilon -optimal, they seem to be practically feasible only when a set of W objects is small. The last solution, which uses a novel learning automaton, demonstrates an excellent partitioning capability. Experimentally, this solution converges an order of magnitude faster than the best known algorithm in the literature.