Elevator Car Assignment Algorithm Limiting Passenger Stops
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Solution Overview
Problem
Existing elevator car assignment strategies fail to effectively limit the number of stops each passenger experiences from their departure floor to their destination floor, impacting passenger satisfaction and system efficiency.
Innovation Solution
A method where elevator cars are ranked based on criteria such as wait time, in-car time, and number of assigned passengers, and passengers are assigned to qualified cars that can limit their stops to a desired maximum, ensuring optimal routing and reduced passenger wait times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If elevator cars are assigned based solely on minimizing wait time, then passenger satisfaction is improved, but the number of stops per passenger increases
Solution Approach 1:
The system changes the assignment parameters from solely wait-time minimization to a multi-parameter evaluation that includes wait time, in-car time, and number of stops. By introducing these additional parameters into the assignment algorithm, the system achieves a balanced optimization that limits stops to a desired maximum while still minimizing wait time, resolving the contradiction between speed and operational simplicity.
2Loss of energy
If elevator cars are assigned to minimize travel distance or energy consumption, then system efficiency is improved, but passenger wait time increases
Solution Approach 1:
The system modifies the assignment criteria by incorporating wait time, in-car time, and number of stops as key parameters. This multi-parameter approach allows the system to balance energy efficiency with passenger satisfaction, ensuring that assignments optimize both system performance and passenger experience rather than focusing on a single metric.
3Ease of operation
If the elevator system accommodates all passenger requests without stop limits, then passenger satisfaction is improved, but system complexity increases
Solution Approach 1:
The system introduces a desired maximum number of stops as a parameter in the assignment algorithm. By defining this threshold, the system simplifies the decision-making process while maintaining passenger satisfaction. The algorithm automatically evaluates candidate cars against this parameter, reducing the need for complex manual intervention or overly sophisticated optimization techniques.
Data Source
AI summary
An exemplary method of controlling an elevator system includes determining that a new passenger requests elevator service from a departure floor to a destination floor. Any candidate elevator cars are ranked. A number of stops for each assigned passenger for a ranked candidate elevator car is determined if the new passenger were assigned to that car. A determination is made whether any ranked candidate elevator car is a qualified car that can accept the new passenger and limit a number of stops for each passenger assigned to that car to a desired maximum number of stops. The new passenger is assigned to a qualified car that has a most favorable ranking of any qualified cars.