In view of the different probability of residents of different floors in high-rise buildings taking the elevator during the peak period of a day, this paper proposes an optimization scheduling model based on Monte Car...
详细信息
ISBN:
(数字)9781728143231
ISBN:
(纸本)9781728143231;9781728143224
In view of the different probability of residents of different floors in high-rise buildings taking the elevator during the peak period of a day, this paper proposes an optimization scheduling model based on Monte Carlo Algorithm, making the existing model more accurate. The automaticcountingmodule (ACM) based on infraredsensor is used to measure and record the number of passengers on different floors. On the basis of a large amount of data obtained from the research, the probability of taking the elevator is calculated, and the cubic polynomial fitting curve is generated based on the least square method, which is applied to the implementation of Monte Carlo Algorithm, and an optimized elevator scheduling model is obtained. At the same time, the optimized model and the existing model are compared in different aspects to generate visual comparison result. In the hypothesis of this paper, under the condition that the number of floors is 20 and the number of households on each floor is 50, the existing model will have a relative error of 10%-20%, and the number of passengers transported by the elevator below 10 floors will be significantly reduced with a relative error of more than 10%. At last, from the elevator scheduling model, a "one-to-many" model can be abstracted. We find that the model optimization idea used in this problem has certain guiding significance in dealing with some other practical problems.
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