一种改进的遗传算法及其在电梯群控中的应用

Multi-objective Optimization of Elevator Group Control using a Modified Genetic Algorithm

以电梯群为群控对象,提出了基于改进的遗传算法系统解决方案;采用权向量整体优化方法,得到最优目标函数值,并由此确定了群控对象目标评价函数,提出了一种基于保存策略进化模型(Elitist Model)的遗传算法求解电梯群控问题的方法.算例及仿真结果对比表明,该方法在小规模应用中,与以往算法相比并无明显优势;但在较大规模的电梯群控仿真中,能效降电梯乘客的等待时间和电梯系统能耗.

Proposed a modified genetic algorithm for the Elevator Group Control problem based Elitist Model. Four overall optimization objective functions were established. Examples and simulation results show that, though the new approach did not have significant advantages comparing to the previous studies in small scale simulation, it outperformed the benchmark in large scale testing and reduced the passenger waiting time and system energy consumption.