Sorting-Based Supply Assignment for Order Fulfillment
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Solution Overview
Problem
Operations management systems face challenges in minimizing unmet demands due to short supply shortages, leading to increased customer dissatisfaction and administrative burdens, as existing algorithms like 'eager' or 'greedy' methods fail to efficiently allocate supplies to demands, resulting in excessive unmet demands.
Innovation Solution
A sorting-based supply assignment system that rapidly determines the minimal cost configuration matching supplied units to demands by prioritizing higher priority orders and using a graphical user interface to visually represent and manipulate scheduled supplies and demands, allowing for drag-and-drop functionality to optimize order fulfillment in short supply situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If 'eager' or 'greedy' algorithms are used to assign available supply to demands, then the allocation process is simple and fast, but the number of unmet demands increases unnecessarily
Solution Approach 1:
The system performs preliminary actions by sorting demands in advance before allocation begins. Demands are sorted by priority level and then by size within each priority level, creating an optimized sequence for supply assignment. This preliminary sorting enables the allocation algorithm to systematically fulfill higher priority and smaller demands first, maximizing the number of met demands without requiring complex real-time optimization during the allocation process itself.
2Manufacturing precision
If supply is allocated to meet large demands first, then individual demand satisfaction is maximized, but the total number of unmet demands increases
Solution Approach 1:
The system applies different allocation strategies to different segments of demands based on their priority levels. High-priority demands receive preferential treatment in the allocation process, while lower-priority demands are allocated from remaining supply. Within each priority level, smaller demands are satisfied first. This segmented, priority-based approach ensures that critical demands are met while maximizing overall fulfillment from limited supply.
Solution Approach 2:
The allocation process is segmented into multiple priority levels, with each level processed separately in sequence. Demands are divided into groups based on priority (e.g., Priority 1, Priority 2, etc.), and supply is allocated to each group in turn. This segmentation allows the system to systematically satisfy higher-priority demands before addressing lower-priority ones, optimizing the overall fulfillment rate under supply constraints.
3Device complexity
If partial filling of demands is not allowed, then supply allocation is simpler, but more supply remains unused when demands cannot be fully met
Solution Approach 1:
The system implements partial filling of demands as an intermediate step in the allocation process. When supply is insufficient to meet a demand completely, the algorithm partially fulfills it and carries forward the remaining supply to subsequent demands. This partial action approach prevents supply from being left unused while maintaining relatively simple allocation rules, as it only requires modifying the standard all-or-nothing allocation logic to allow partial allocations.
Data Source
AI summary
Systems, methods, and other embodiments for sorting-based assignment to optimize order fulfillment with short supply. One embodiment includes identifying a set of one or more distributions within a series of days. Sorting all demands of a first priority level occurring in the series of days by ascending order of size of the demand. For each demand of the first priority level in sorted order, (a) selecting an initial distribution during which the demand is scheduled to be fulfilled from the set of distributions, and (b) generating an indication that the demand can cannot be completely fulfilled, based on the size of the demand and the amount of supply available. Automatically arranging a graphical representation of a schedule of supplies and met and unmet demands for the series of days in a graphical user interface based at least on the indications generated for each demand.