Inventory Allocation Optimization with Constrained Safety Stock
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Solution Overview
Problem
Existing inventory management systems fail to efficiently allocate items across a supply chain while respecting budget constraints and maximizing expected profits, as they do not explicitly consider target service levels and supply chain structure.
Innovation Solution
A method that determines baseline inventory levels based on demand and lead time, calculates total time-phased inventory and target safety stock levels, and establishes constrained safety stock levels considering user-defined inventory, budget, and capacity constraints, to optimize inventory allocation across multiple locations in a supply chain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing inventory management systems use local optimization heuristics to allocate items, then the allocation process is simple and fast, but the service levels are not optimized and budget constraints are not effectively respected
Solution Approach 1:
The patent segments the supply chain into multiple locations and items, then applies linear programming to optimize inventory allocation across all segments simultaneously rather than using local heuristics at each location independently. This global optimization approach respects budget constraints while maximizing service levels across the entire supply chain network.
Solution Approach 2:
The patent changes the optimization parameters by explicitly incorporating service level targets and budget constraints into the linear programming model. Instead of using fixed heuristic rules, the system dynamically adjusts inventory allocation based on varying service level requirements, demand patterns, and budget availability across different locations and time periods.
2Ease of operation
If inventory planners apportion budget a priori among item classes based on historical data, then the allocation process is straightforward, but the solution does not maximize expected profits or achieve target service levels
Solution Approach 1:
The patent transforms static, historical budget allocation into a dynamic optimization process. The linear programming model continuously adjusts inventory allocation based on current demand forecasts, service level targets, and budget constraints, allowing the system to adapt to changing conditions and maximize expected profits rather than relying on fixed historical patterns.
Solution Approach 2:
The system incorporates feedback loops where service level achievements and budget utilization are continuously monitored and fed back into the optimization model. This allows inventory planners to adjust allocations in subsequent periods based on actual performance, creating a closed-loop system that progressively improves profit maximization while meeting service level targets.
3Reliability
If inventory levels are increased to meet higher service level targets, then customer service improves, but inventory costs and budget consumption increase
Solution Approach 1:
The patent uses parameter changes by allowing the optimization model to dynamically determine the optimal service level achievement for each location and item based on the budget constraint. Instead of uniformly increasing inventory across all locations to meet target service levels, the system adjusts safety stock levels and service level achievements to maximize overall profitability while staying within budget limits.
Solution Approach 2:
The patent applies local quality by allowing different service level achievements at different locations based on their specific characteristics, demand patterns, and profitability contributions. High-profit locations may achieve higher service levels with more inventory, while lower-profit locations accept lower service levels with less inventory, optimizing the overall balance between service level and inventory cost across the supply chain.
Data Source
AI summary
Systems, methods, and machine-readable media are disclosed to allocating inventory across a plurality of locations in a supply chain. In one embodiment, a method comprises determining a total time-phased inventory and target safety stock level for each of the items at each location based on the baseline inventory as determined from expected demand and lead times for each item at each location, a target service level, a demand uncertainty level, a lead time uncertainty level, carrying costs in the supply chain and user constraints on budget, capacity and inventory.