Collaborative Logistics Map for Multi-Supplier Delivery Scheduling
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Solution Overview
Problem
Collaborative logistics between multiple supplier organizations is hindered by constraints such as location, collaborative, and product constraints, which prevent them from transporting goods together using the same fleet of delivery vehicles, leading to increased logistics costs and inefficient delivery schedules.
Innovation Solution
A logistics management platform generates a collaborative logistics map that includes route information, location constraints, collaborative constraints, and product constraints, determining delivery schedules that avoid conflicts and optimize routes for a fleet of delivery vehicles associated with a delivery organization, allowing multiple supplier organizations to share deliveries and reduce transportation costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple supplier organizations use separate delivery vehicles for their own deliveries, then each organization can maintain full control over their delivery schedules and routes, but transportation costs increase and logistics efficiency decreases
Solution Approach 1:
The patent combines multiple delivery schedules from different supplier organizations into a single collaborative delivery schedule. The system merges delivery requests from multiple suppliers into unified routes that serve multiple customers, allowing delivery vehicles to consolidate goods from different suppliers and deliver to multiple destinations in optimized sequences, thereby improving logistics efficiency while managing complexity through automated scheduling algorithms
Solution Approach 2:
The delivery vehicle is designed to perform multiple functions by serving multiple supplier organizations and multiple customer locations. A single delivery vehicle can carry goods from different suppliers and deliver to various destinations, making the vehicle universal in its capability to handle diverse delivery requirements rather than being dedicated to a single supplier-route combination
2Productivity
If multiple supplier organizations share the same delivery vehicles, then transportation costs are reduced and logistics efficiency improves, but constraints such as location, collaborative, and product constraints create scheduling conflicts
Solution Approach 1:
The system implements feedback mechanisms where the scheduling algorithm continuously evaluates delivery schedules against location constraints, collaborative constraints, and product constraints. When conflicts are detected, the system provides feedback to adjust the schedule, resequence deliveries, or modify vehicle assignments to resolve constraint violations while maintaining overall logistics efficiency
Solution Approach 2:
The delivery schedule is designed to be dynamic and adaptable rather than fixed. The system can dynamically adjust delivery sequences, vehicle assignments, and route optimizations in response to changing constraints and conditions, allowing the schedule to flexibly accommodate location restrictions, supplier collaboration requirements, and product-specific constraints
3Loss of time
If delivery vehicles follow optimized routes to avoid constraints, then transportation time and costs are reduced, but processing resources are consumed in generating and managing complex delivery schedules
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing optimized delivery schedules, route information, and constraint data in a collaborative logistics map before actual deliveries occur. This advance preparation allows the system to quickly retrieve and execute pre-optimized routes during actual deliveries, reducing real-time processing requirements and minimizing delivery time while the computational resources are consumed during the offline schedule generation phase
Data Source
AI summary
A device may generate a product delivery map that includes route information that is to be used by a fleet of delivery vehicles for performing a set of deliveries, and a set of location constraints identifying locations that are to be avoided by the fleet of delivery vehicles when performing the set of deliveries. The device may generate a collaborative interactions map that includes a set of collaborative constraints indicating particular supplier organizations that are candidates to engage in collaborative logistics. The device may determine, based on the set of location constraints and the set of collaborative constraints, a set of delivery schedules that are to be used to perform the set of deliveries. The device may provide the set of delivery schedules to one or more devices associated with the delivery organization to allow the fleet of delivery vehicles to perform the set of deliveries.