Multi-Type Order Fulfillment Assignment via Flexibility Metric
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Solution Overview
Problem
Classic solvers like Simplex are unable to provide assignment solutions in real-time for operations management systems dealing with limited resource supplies and multiple item types, due to their linear nature and inability to parallelize.
Innovation Solution
A multi-type source assignment system that uses a novel flexibility metric to make real-time assignments between orders for multiple item types and candidate locations, prioritizing locations with the lowest flexibility to maximize order fulfillment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If classic solvers like Simplex are used for resource assignment, then assignment accuracy is maintained, but processing speed becomes too slow for real-time operations
Solution Approach 1:
The patent segments the resource assignment problem into multiple independent sub-problems, each representing a subset of orders or resources. This allows parallel processing of segments while maintaining overall assignment accuracy, thereby achieving both real-time speed and precise allocation.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing resource availability, order requirements, and assignment rules in structured data formats. This preprocessing enables rapid real-time assignment decisions without sacrificing accuracy, as the heavy computational work is done in advance.
2Reliability
If classic solvers are used for assignment optimization, then optimal solutions are found, but the linear nature prevents parallel processing
Solution Approach 1:
The patent divides the optimization problem into independent segments that can be processed in parallel. Each segment maintains the essential constraints and objectives, allowing multiple processors to work simultaneously while collectively achieving the global optimal solution.
Solution Approach 2:
The system creates a universal assignment framework that can handle multiple types of resources, orders, and constraints through a standardized parallel processing architecture. This multi-functional design allows the same parallel structure to solve various assignment problems while maintaining optimization quality.
3Loss of time
If real-time assignment generation is implemented, then operational responsiveness is improved, but computational complexity increases for multi-type orders
Solution Approach 1:
The patent performs preliminary actions by pre-structuring order data, resource data, and assignment rules into optimized data formats with pre-computed indices and constraints. This preparation reduces the computational complexity of real-time processing, enabling rapid assignment generation for multi-type orders.
Solution Approach 2:
The system creates simplified copies or representations of the complex assignment problem that can be processed rapidly in real-time. These copies maintain the essential assignment logic and constraints but use streamlined data structures and algorithms suitable for fast computation.
Data Source
AI summary
Systems, methods, and other embodiments associated with selection of supply locations from among multiple candidate locations in order to maximize fulfillment of orders that include multiple item types when there is a shortage of one or more of the item types are described. In one embodiment, a method includes accessing a plurality of orders that include multiple types of items and a plurality of candidate locations for fulfilling the orders. Candidate locations are then selected to fulfill individual orders based on finding the one of the candidate locations that has a lowest value for a flexibility metric. A user interface is generated to display the assignments. In response to a request to finalize the assignments, allocation instructions are generated to allocate the multiple types of items to the orders in accordance with the finalized instructions.