针对乘客候梯时间,乘梯时间,拥挤度和电梯系统运行能耗等多个目标优化的电梯群问题,给出一个改进的遗传算法。该算法在选择,交叉,变异操作时,采用首位存在最优个体,在生成初始种群时采用模糊生成其中一个解的方法。并把改进的遗传算法应用到实际电梯群控中,数值结果表示该方法是有效的,可行的。 An improved genetic algorithm is proposed for multiple objectively optimized elevator group problems such as passenger waiting time, riding time, congestion degree and energy consumption of elevator system. In the selection, crossover and mutation operations, the algorithm adopts the method of generating the optimal individuals first and generating one of the solutions by fuzzy when generating the initial population. The improved genetic algorithm is applied to the actual elevator group control. Numerical results show that this method is effective and feasible.