基于GNP的多轿厢电梯多目标优化算法

Multi-car Elevator and Multi-objective Optimization Algorithm Based on GNP

"一井多梯"多轿厢电梯是当前国际上解决高层建筑输送效率、减小占地面积、节约能源和减少建筑成本的最新方式.针对多轿厢电梯多目标优化问题进行深入研究,结合遗传算法GA和遗传规划GP的特点,探讨了电梯优化调度控制系统的适应度函数选取、种群初始化和GNP节点设置问题,并通过选择、交叉、变异算法计算,研究了GNP对于多轿厢多目标的优化性能,以候梯时间、乘梯时间、乘客人数、系统能耗为目标,提出一种改进的基于GNP的多轿厢电梯优化调度算法及策略,对比改进前的GNP算法,进行了实验仿真分析,实验结果验证了改进后的GNP新方法的有效性,对多轿厢多目标优化的可实现性和优越性.

＂ One shaft, Multi-cars＂ elevator is the new way of vertical transportation. It can raise transportation efficiency, save area and energy, reduce construction cost. In this paper, further researched multi-car and multi-objective optimization, combined with the advantages of GA（ Genetic Algorithm} and GP（ Genetic Programming）, discussed how to select fitness function, population initial- ization and set GNP notes. By mean of selection, crossover and mutation, researched GNP optimization performance of multi-car and multi-objective. Then, an optimization scheduling strategy has been put forward based on imoroved GNP, which with the waiting time, taking time, passenger numbers and energy cost as optimization objective. The simulation has been done, and compared with the traditional GNP, the results has proved improved GNP optimization scheduling of multi-car and multi-objective is feasible and superior.