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Convergence Refinement of Stochastic Optimization by Coupling a Genetic Algorithm and a Simulated Annealing Procedure

机译:遗传算法与模拟退火程序耦合对随机优化的收敛细化

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摘要

Numerous trials have to be carried out to refine the convergence of Simulated Annealing (SA) and Genetic Algorithms (GAs). A procedure that couples both GAs and SA algorithms using the ability of GAs to reach quite optimal solutions, and SA procedure for scanning the neighboring solutions to efficiently improve the objective function value. The probability of reaching the true optimal solution, can be significantly increased by this coupling. This approach is illustrated by the problem of synthesis of distillation sequences of mixtures involving 10 to 16 hydrocarbons.
机译:必须进行大量试验以完善模拟退火(SA)和遗传算法(GA)的融合。利用GA达到最佳解的能力,将GA和SA算法结合起来的过程,以及用于扫描相邻解以有效提高目标函数值的SA过程。通过这种耦合可以显着提高达到真正最佳解的可能性。通过涉及10至16个烃的混合物的蒸馏序列的合成问题来说明该方法。

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