Tour Optimization System for Load Assignment
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Solution Overview
Problem
Current systems for managing and optimizing tours in carrier delivery services are inadequate, failing to automatically place loads on dedicated tours or short haul shuttle routes, and do not analyze past transportation patterns for cost savings, leading to inefficiencies in transporting large volumes of goods.
Innovation Solution
A method and system that evaluates and ranks load data against available segments, automatically assigning loads to optimize tour routes, utilizing recent load history to analyze and generate optimal routes, and recommending dedicated tours over common carriers for cost savings, with features for automatic tour building and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If planners manually schedule loads to tours using existing systems, then load placement can be performed, but transportation costs are not optimized and efficiency is lost due to inadequate analysis of transportation patterns
Solution Approach 1:
The system performs preliminary analysis of transportation patterns and pre-identifies optimal tour assignments before loads need to be scheduled. By analyzing historical data and predicting future transportation needs, the system prepares optimized tour recommendations in advance, allowing planners to implement cost-effective solutions without manual analysis of each load placement decision.
2Ease of operation
If planners use existing systems to manage tours, then basic tour creation is possible, but automatic optimization and pattern analysis are not performed
Solution Approach 1:
The system performs self-service by automatically analyzing transportation patterns, generating optimized tour recommendations, and identifying cost-saving opportunities without requiring planner intervention. The system serves itself by continuously learning from historical data and automatically improving tour assignments, while planners only need to review and approve the automatically generated recommendations.
3Loss of time
If planners evaluate multiple tour options manually, then load placement decisions can be made, but time is lost due to the complexity of analyzing multiple segments and carriers
Solution Approach 1:
The system provides feedback to planners by automatically evaluating multiple tour options and presenting the optimal assignments with supporting analysis. The system continuously monitors transportation patterns and provides feedback on cost savings achieved, allowing planners to make informed decisions quickly while maintaining high reliability in cost optimization through data-driven recommendations.
Data Source
AI summary
A method for optimizing a tour having a first segment with an origination point and a destination point and a second segment with an origination point and a destination point. The method comprises: receiving first load data about a first load and second load data about a second load; evaluating a fit of the first load data on the first segment and a fit of the second load data on the first segment; evaluating a fit of the first load data on the second segment and a fit of the second load data on the second segment; ranking the relative fits of the first load data and the second load data against the first segment on a first segment list; ranking the relative fits of the first load data and the second load data against the second segment on a second segment list; assigning the load having the highest ranking fit from the first segment list to the first segment and removing that load from the second segment list; and assigning the load having the highest ranking fit from the second segment list to the segment.