Goods Transportation Using Dynamic Last-Mile Regional Units
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Solution Overview
Problem
The delivery industry faces challenges in efficiently managing varying quantities of delivery items across different areas and time periods, leading to issues such as delivery delays and transporter overwork due to arbitrary assignment of personnel without considering fluctuations in demand.
Innovation Solution
A system and method that determines optimal regional units for last-mile delivery based on information about delivery places, goods quantities, transportation times, and transporter capabilities, and assigns transporters accordingly to optimize delivery operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If transporters are arbitrarily assigned to predetermined areas, then the assignment process is simple, but delivery efficiency deteriorates due to inability to respond to varying delivery quantities and times
Solution Approach 1:
The patent implements dynamic transporter assignment by continuously monitoring delivery quantity and time data, then adjusting regional unit boundaries and transporter allocations in real-time. The system calculates optimal regional units based on current delivery demands and reassigns transporters accordingly, transforming the static arbitrary assignment into a dynamic optimization process that adapts to varying conditions.
Solution Approach 2:
The patent changes the parameters of assignment by using delivery quantity and time as key variables to determine regional unit boundaries and transporter assignments. Instead of fixed geographic boundaries, the system adjusts regional definitions based on actual delivery characteristics, thereby optimizing the match between transporter capacity and delivery demands.
2Device complexity
If the number of transporters per area is fixed, then management is simplified, but transporter overwork occurs during peak delivery periods
Solution Approach 1:
The system dynamically adjusts the number of active transporters and regional unit boundaries based on real-time delivery quantity data. During peak periods, the system creates additional regional units or reassigns existing transporters to high-demand areas, preventing overwork. The management complexity is offset by automated calculations that continuously optimize transporter allocation without manual intervention.
Solution Approach 2:
The patent implements a feedback mechanism where delivery quantity and time data are continuously collected and used to adjust transporter assignments. The system monitors actual delivery performance and uses this feedback to reallocate transporters, ensuring balanced workloads during peak periods while maintaining simplified management through automated control loops.
3Ease of operation
If regional units are arbitrarily defined, then the system is simpler to operate, but delivery time increases due to suboptimal transporter assignment
Solution Approach 1:
The patent changes the definition of regional units from arbitrary geographic boundaries to data-driven regions based on delivery quantity and time parameters. The system calculates optimal regional units that minimize delivery time by grouping areas with similar delivery characteristics, thereby reducing delivery time while maintaining operational simplicity through automated region creation and assignment.
Solution Approach 2:
The system performs preliminary calculations to determine optimal regional units and transporter assignments before actual delivery occurs. By pre-calculating the best assignment based on historical delivery data and current demands, the system prepares optimized routes and assignments in advance, reducing delivery time without requiring complex real-time decision-making during delivery operations.
Data Source
AI summary
According to one aspect of the present invention, provided is a method for supporting transportation of goods. The method includes the steps of: acquiring at least one of information on a delivery place or collection place and a quantity of goods to be transported, and information on an amount of time required for transportation of the goods; and determining at least one optimal regional unit where last-mile delivery of the goods is to be performed, on the basis of the acquired information.