Dispatch Control Stochastic Scheduling for Mobile Units
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Solution Overview
Problem
Existing dispatch systems face challenges in accurately controlling the geographical positions of mobile units due to uncertainty and unpredictability in the physical world, such as traffic, weather, and equipment conditions, which nonlinear and dynamic environments complicate deterministic control methods.
Innovation Solution
A dispatch control system that calculates stochastic characteristics from historical data to generate scheduling processes, including volatility metrics, to optimize the order of attendance for mobile units, allowing for adaptable navigation and reduced uncertainty in attendance times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If deterministic control systems are used to monitor mobile unit movements, then the system structure is simple and easy to implement, but the system cannot accurately account for uncertainty and unpredictability in the physical world such as traffic, weather, and seasonal variations
Solution Approach 1:
The patent applies dynamics by transitioning from static deterministic control to dynamic stochastic control that adapts to changing conditions. The system uses stochastic characteristics and volatility metrics that are calculated dynamically based on historical data and updated in real-time to reflect uncertainty and unpredictability in the physical world, allowing the control system to respond to varying traffic, weather, and seasonal conditions.
Solution Approach 2:
The patent implements feedback mechanisms by calculating volatility metrics based on historical attendance data and using this information to adjust future scheduling decisions. The system continuously monitors actual attendance times compared to scheduled times, updates stochastic characteristics, and refines the order of attendance to minimize volatility, creating a closed-loop control system that learns from past performance.
2Reliability
If the system accounts for uncertainty and unpredictability by using stochastic characteristics and volatility metrics, then the reliability of geographical position control is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The patent applies preliminary action by calculating stochastic characteristics and volatility metrics in advance based on historical data before generating the optimized order of attendance. The system pre-computes the probability distributions and uses these pre-calculated values to determine the optimal scheduling sequence, reducing the need for complex real-time computations during operation.
Solution Approach 2:
The patent changes parameters by transforming deterministic scheduling parameters into stochastic parameters that account for uncertainty. The system uses probability distributions to represent attendance durations and calculates volatility metrics as key parameters, allowing the optimization process to work with statistical parameters rather than fixed values, thereby capturing the essence of unpredictability in a manageable form.
3Loss of time
If the system optimizes the order of attendance based on volatility metrics, then the variability in travel and attendance times is reduced, but the computational effort and processing time increase
Solution Approach 1:
The patent applies segmentation by breaking down the complex optimization problem into manageable components: first calculating stochastic characteristics for individual geographical positions, then computing volatility metrics for each position independently, and finally using these segmented results to determine the optimal order of attendance. This modular approach reduces computational complexity compared to optimizing the entire schedule as a single complex problem.
Data Source
AI summary
A dispatch control system includes a data store with records of previously-attended geographical positions of a mobile unit indicating at least a duration of attendance. The dispatch control system is configured to calculate one or more stochastic characteristics for the durations of attendance representative of a variability of the durations of attendance at said past geographical positions, and generate data indicative of an order of attendance for the mobile unit based on travel and estimated durations of attendance. This data is re-ordered and volatility metrics for each set of modified data are determined. The set of volatility metrics is used to modify the data indicative of an order of attendance for the mobile unit. The dispatch control system is configured to transmit to the mobile unit data indicative of geographical positions corresponding to said modified generated data for use in generating routing instructions.