Multi-Source Supply Assignment via Greedy Demand Sorting
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Solution Overview
Problem
Existing operations management systems face challenges in efficiently assigning supplies to demands from multiple sources, especially when supply is limited, as standard solvers like Simplex become computationally expensive and unable to provide solutions in a timely manner, especially for complex scenarios.
Innovation Solution
A multi-source assignment system that sorts demands by size and priority, identifies sufficient supply sources, and allocates supplies interactively, using algorithms like Flexibility Score and Multi-Flexibility Score to optimize supply allocation, enabling real-time 'what-if' explorations and near-optimal solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard solvers like Simplex are used to solve supply to demand assignment problems, then optimal solutions can be found, but computational time and memory requirements become excessively large for complex scenarios
Solution Approach 1:
The patent segments the supply to demand assignment problem into multiple independent steps: sorting demands by size and priority, identifying sufficient supply sources, and making greedy allocations. This decomposition transforms the complex combinatorial optimization problem into a series of simpler, manageable operations that can be executed efficiently without requiring full optimization solvers.
Solution Approach 2:
The patent applies a greedy algorithm that makes locally optimal choices at each step (assigning supply to the smallest demand first, then to largest) rather than searching for the globally optimal solution. This partial action approach sacrifices some optimality guarantees but dramatically reduces computational time and resource requirements, providing near-optimal solutions for complex scenarios.
2Reliability
If standard solvers like Simplex are used to solve supply to demand assignment problems, then solutions can be obtained, but memory resources are exhausted before arriving at a solution
Solution Approach 1:
The patent segments the problem-solving process into sequential operations that process demands one at a time in sorted order. This eliminates the need for Standard solvers to simultaneously consider all possible combinations of supply and demand assignments, thereby reducing memory requirements from exponential to linear scale.
Solution Approach 2:
The patent extracts the essential decision-making logic from complex optimization solvers by implementing a custom greedy algorithm that directly processes demands in sorted order. This extraction eliminates unnecessary computational overhead and memory consumption associated with standard solver frameworks while retaining the core assignment functionality.
3Adaptability or versatility
If the number of ways to fill demands is considered, then all possible assignments can be enumerated, but the growth is combinatorial making the problem hard in computing
Solution Approach 1:
Instead of enumerating all possible assignments and then selecting the best one (the conventional approach), the patent inverts the approach by directly constructing a valid assignment through greedy selection. By processing demands in sorted order and making immediate allocation decisions, the algorithm avoids the combinatorial explosion of enumerating all possibilities while still achieving adaptable and versatile assignment outcomes.
Data Source
AI summary
Systems, methods, and other embodiments associated with assigning supply to demand from multiple supply sources are described. In one embodiment, a method includes sorting a set of demands by size of demand. A set of assignments between demands belonging to the set of demands and supplies at multiple sources is generated. The set of assignments is generated by, for the demands in ascending order of the size of demand, identifying from among the multiple sources a set of sources having sufficient supply to fill the demand, choosing one source from the set of sources from which to fill the demand, and assigning the demand to be filled from one or more supplies of the one source to form an assignment for the demand in the set of assignments. Supplies are allocated to the demands belonging to the set of demands in accordance with the set of assignments.