Dynamic Delivery Route Shuffling Using Cost Differential Evaluation
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Solution Overview
Problem
Current delivery route optimization systems face challenges in efficiently utilizing fleet vehicle capacity and third-party delivery networks, particularly due to the computational complexity of NP-hard problems, leading to limitations in route optimization and increased costs.
Innovation Solution
A system and method that dynamically shuffles fleet delivery routes by evaluating cost differentials between removing orders from existing routes and inserting them into third-party delivery routes, using a randomized node movement approach to optimize delivery routes and communicate orders to third-party deliverers when cost savings are achieved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional fleet vehicle routing systems are used, then delivery routes can be determined, but the system is limited by fleet availability and capacity, leading to higher costs and reduced optimization
Solution Approach 1:
The patent combines the retailer's private fleet with third-party delivery networks into a unified routing system. The system integrates multiple delivery resources (fleet vehicles and third-party deliverers) to work together on the same delivery routes, allowing flexible allocation of delivery capacity while maintaining a single optimized route structure.
Solution Approach 2:
The routing system is designed to handle multiple types of delivery resources universally. It can assign orders to either fleet vehicles or third-party deliverers based on real-time availability, capacity, and cost considerations, making the system adaptable to different delivery scenarios without requiring separate routing systems for each resource type.
2Productivity
If fleet vehicle capacity is increased to handle more deliveries, then delivery capacity improves, but fleet availability and operational costs increase
Solution Approach 1:
The system introduces a routing optimization platform as an intermediary that coordinates between the retailer's fleet and third-party delivery networks. This intermediary manages order allocation dynamically, assigning deliveries to the most appropriate resource based on current capacity and cost, thereby increasing effective delivery capacity without proportionally increasing fleet size.
Solution Approach 2:
The system dynamically changes the parameter of delivery resource allocation by transitioning from a static fleet-only model to a dynamic model that adjusts the mix of fleet vehicles and third-party deliverers based on real-time conditions such as order volume, delivery locations, time windows, and cost parameters.
3Adaptability or versatility
If more third-party deliverers are integrated into the system, then delivery flexibility improves, but route optimization complexity increases due to NP-hard computational problems
Solution Approach 1:
The routing system segments the delivery network into discrete, manageable components including individual delivery routes, specific delivery locations, and distinct time windows. This segmentation allows the system to process and optimize routes in smaller units rather than attempting to optimize the entire network simultaneously, reducing computational complexity while maintaining flexibility.
Solution Approach 2:
The system implements partial optimization by focusing on optimizing individual routes and segments rather than attempting to optimize the entire delivery network at once. It applies optimization to subsets of orders and routes where improvements can be made without requiring complete re-optimization of all deliveries, thereby reducing computational burden while still achieving versatility.
Data Source
AI summary
Systems and methods including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform functions comprising: determining at least one fleet delivery route for delivery of one or more items of one or more orders to one or more locations using a vehicle fleet; dynamically shuffling the at least one fleet delivery route by at least evaluating a cost differential; when the cost differential satisfies a threshold: removing the first order from the source route; inserting the first order into the first other delivery route; and communicating the first order to a first other deliverer associated with the first other delivery route. Additional embodiments are disclosed herein.