Multi-Vehicle Scheduling via Coordination Impact Correction
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Solution Overview
Problem
Current vehicle scheduling systems face challenges with vehicle route conflicts and congestion when multiple vehicles are involved in logistics transportation, leading to low completion efficiency of transportation tasks.
Innovation Solution
A multi-vehicle coordination-based vehicle scheduling system that includes a parameter module for determining scheduling parameters, a scheduling module for generating scheduling results, a coordination module for assessing coordination impact values, and a correction module for adjusting parameters based on these values to optimize vehicle routes and reduce congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple vehicles are used to complete transportation tasks, then transportation capacity is improved, but vehicle route conflicts and congestion occur
Solution Approach 1:
The system segments the transportation task completion process by assigning different sequence orders to different vehicles. The scheduling module divides overall transportation tasks into sub-tasks with defined execution sequences, allowing multiple vehicles to operate simultaneously without conflicts by coordinating their action orders.
Solution Approach 2:
The coordination impact value calculation module implements feedback by continuously evaluating the coordination state of multiple vehicles and calculating impact values based on scheduling results. This feedback mechanism allows the system to adjust scheduling parameters dynamically to avoid route conflicts and congestion while maintaining high transportation capacity.
2Productivity
If traditional scheduling methods are used, then scheduling simplicity is maintained, but task completion efficiency is low
Solution Approach 1:
The scheduling module performs preliminary actions by pre-determining scheduling parameters including sequence orders for multiple vehicles before task execution. By establishing the coordination framework and task assignment in advance, the system enables efficient multi-vehicle operation without requiring complex real-time coordination during execution.
Solution Approach 2:
The coordination impact value calculation module acts as an intermediary that evaluates scheduling results and provides feedback for optimization. This intermediary mechanism bridges the gap between simple scheduling decisions and efficient task completion by systematically assessing coordination effects without requiring complex direct control between vehicles.
3Measurement precision
If coordination impact value correction is implemented, then scheduling accuracy is improved, but computational complexity increases
Solution Approach 1:
The correction module implements partial correction by adjusting scheduling parameters based on coordination impact values only when necessary. Rather than continuously recalculating all parameters, the system applies corrections selectively to maintain scheduling accuracy while avoiding excessive computational overhead from unnecessary recalculations.
Data Source
AI summary
A multi-vehicle coordination-based vehicle scheduling system and method, an electronic apparatus, and a storage medium. The scheduling system includes a parameter module configured for determining a scheduling parameter; a scheduling module configured for determining a scheduling result; a coordination module configured for determining a coordination impact value; a correction module configured for correcting the scheduling parameter, the correction module judging whether the coordination impact value is no less than a preset threshold, correcting the scheduling parameter based on a judgment result that the coordination impact value is no less than the preset threshold, and re-determining the scheduling result and the coordination impact value based on the corrected scheduling parameter; and an output module configured for outputting the scheduling result based on the judgment result that the coordination impact value is less than the preset threshold. Sequence order and task assignment problems when scheduling multiple vehicles are effectively solved.