热力学遗传算"~-(therm odynamical genetic algorithms，简称TDGA)借鉴固体退火过程中能量与熵的竞争

模式来协调GA 中“选择压力”和“种群多样性”之间的冲突．然而TDGA 目前极高的计算代价限制了其应用．为了提

高TDGA的计算效率，首先定义一种等级熵(rating—based entropy,J~j称RE)度量方法，它能以较小的计算成本度量种

群中个体适应值的分散程度．然后引入分量热力学替换规则(component thermod)rnamical replacement，简称CTR)，有

效地降低了替换规则的复杂度．同时也证明了CTR规则具有驱动种群自由能近似最速下降的能力．在0．1背包问题

上的实验结果表明，RE 方法和CTR规则在保持TDGA良好的性能与稳定性的同时，极大地提高了其计算效率．-Thermodynamical genetic algorithms(TDGA)simulate the competitive model between energy and

entropy in annealing to harmonize the conflicts between selective pressure and population diversity in GA．But high

computational cost restricts the applications of TDGA．In order to improve the computational efi ciency，a

measurement method of rating—based entropy(RE)is proposed．The RE method can measure the fitness dispersal

with low computational cost．Then a component therm odynamical replacement(CTR)rule is introduced to reduce

the complexity of the replacement，and it is proved that the CTR rule has the approximate steepest descent ability of

the population free energy．Experimental results on 0-1 knapsack problems show that the RE method and the CTR

rule not only maintain the excellent perform ance and stability of TDGA，but also remarkably improve the

computational efi ciency of TDGA．