Elevator Group Management System Dynamic Weight Allocation
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Solution Overview
Problem
Current elevator group management systems face challenges in accurately forecasting elevator positions and allocating calls due to the lack of consideration for future hall calls and positional relationships between elevators, leading to inefficient waiting times and performance evaluations.
Innovation Solution
The system creates a forecasted trajectory for each elevator's movement over a predetermined period, calculates evaluation values by weighting waiting time and positional relationships, and allocates calls based on a continuously changing weighting function to optimize elevator allocation and maintain even intervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If allocation control is based on forecasted waiting time only, then the waiting time for currently generated hall calls is optimized, but the influence of future hall calls is not sufficiently considered
Solution Approach 1:
The system performs preliminary forecasting of future hall calls and their impact on elevator allocation. By predicting future call patterns and pre-calculating their influence on waiting times, the system prepares allocation decisions that consider both current and future demands, rather than reacting only to present conditions.
Solution Approach 2:
The evaluation function dynamically adjusts between optimizing for current hall calls and anticipating future hall calls based on real-time conditions. The system transitions from static forecasted waiting time calculations to dynamic evaluation that adapts to changing traffic patterns and future call predictions.
2Productivity
If cage allocation is based on forecasted waiting time index, then allocation decisions are made efficiently, but the positional relationship among cages is not taken into consideration
Solution Approach 1:
The system merges two previously separate evaluation aspects: forecasted waiting time and positional relationships among cages. By combining these into a unified evaluation function, the system simultaneously considers both the time efficiency of allocation and the spatial distribution of cages, leading to more comprehensive allocation decisions.
Solution Approach 2:
The evaluation function incorporates additional parameters beyond forecasted waiting time, specifically including positional relationships and intervals among cages. This expansion of evaluation parameters allows the system to optimize allocation based on both temporal and spatial factors.
3Loss of time
If conventional control schemes dispose cages at equal time intervals, then long waiting times are restrained, but the system lacks accuracy in forecasting elevator positions and cannot immediately adjust to changing traffic conditions
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor actual elevator positions and compare them with forecasted positions. Based on this feedback, the system identifies forecast errors and adjusts future predictions accordingly, improving forecast accuracy over time while maintaining the equal time interval disposition strategy.
Solution Approach 2:
The system transitions from static equal time interval disposition to a dynamic approach where the evaluation function can immediately adjust to changing traffic conditions. By incorporating real-time traffic flow information and forecast errors into the evaluation, the system maintains equal time interval benefits while adapting to varying demand patterns.
4Ease of operation
If weights in evaluation function are fixed, then system operation is simple, but the system cannot immediately adjust to changing traffic conditions
Solution Approach 1:
The system changes from fixed weights to dynamically adjustable weights in the evaluation function. The weights are immediately adjustable based on real-time traffic conditions, allowing the system to emphasize different evaluation criteria (such as waiting time versus positional relationships) according to current operational demands.
Solution Approach 2:
The evaluation function parameters, specifically the weights, are made variable rather than fixed. This allows the system to adjust the relative importance of different evaluation factors in response to changing traffic conditions, maintaining operational simplicity while enhancing adaptability.
Data Source
Figure 1(a)~1(c)
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AI summary
A system is provided for supporting a reduction in average waiting time of an elevator group management system, and an evaluation on group management control performance. A forecasted trajectory of each elevator within a predetermined time from a current time point is found and displayed. Also, an evaluation value is calculated for a forecasted interval with respect to a target interval between respective elevators in a predetermined time from the evaluation value, and an elevator is allocated to a generated hall call based on the evaluation value such that the forecasted interval comes closer to the target interval. By displaying the forecasted trajectory of each elevator, it is possible to support the evaluation on the performance of the group management system through clarification of the reason for allocation. Also, the control performance of the group management system is improved, including a reduction in average waiting time, through allocation control close to an ideal one.