Fast Optimization by Demon Algorithms
نویسنده
چکیده
We introduce four new general optimization algorithms based on thèdemon' algorithm from statistical physics and the simulated annealing (SA) optimization method. These algorithms use a computationally simpler acceptance function, but can use any SA annealing schedule or move generation function. Computation per trial is signiicantly reduced. The algorithms are tested on traveling salesman problems including Grotschel's 442-city problem and the results are comparable to those produced using SA. Applications to the Boltzmann machine are considered.
منابع مشابه
Demon Algorithms and their Application to Optimization Problems
We introduce four new general optimization algorithms based on the ‘demon’ algorithm from statistical physics and the simulated annealing (SA) optimization method. These algorithms reduce the computation time per trial without significant effect on the quality of solutions found. Any SA annealing schedule or move generation function can be used. The algorithms are tested on traveling salesman p...
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