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Deterministic learning automata solutions to the equipartitioning problem

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2 Author(s)
Oommen, B.J. ; Sch. of Comput. Sci., Carleton Univ., Ottawa, Ont., Canada ; Ma, D.C.Y.

Three deterministic learning automata solutions to the problem of equipartitioning are presented. Although the first two are ε-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

Published in:

Computers, IEEE Transactions on  (Volume:37 ,  Issue: 1 )

Date of Publication:

Jan 1988

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