Several procedures [l-31 aimed at producing globally optimal solutions were proposed,
but these procedures are impractical for all but small-sized problems. The computational
difficulty has motivated the development of many heuristic algorithms [4-81. Since 1968, the
eight problems defined by Nugent [4] have become the standard benchmark problems for
comparing different techniques.
In this paper, we present a new optimization approach, which we call the Guided
Evolutionary Simulated Annealing (GESA) approach, and report on the results of application
of that to the benchmark problems. Current results compare favorably with previous
benchmarks.
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