Distribution-Independent Inventory Planning With Multiple Service Targets
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Solution Overview
Problem
Existing methods struggle to accurately determine inventory policies that account for non-standard demand distributions, uncertain lead times, and multiple target service levels, leading to inefficiencies in supply chain inventory management.
Innovation Solution
An inventory planner system that generates policies using demand distributions, non-linear cost functions, and multiple service level targets, modeled as a Markov decision process and solved using linear programming, to optimize inventory levels and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional inventory methods are used, then simplicity of implementation is maintained, but accuracy of inventory policy determination deteriorates when facing nonstandard demand distributions, uncertain lead times, and multiple service level targets
Solution Approach 1:
The patent transforms the complex inventory optimization problem into a linear programming framework by changing the mathematical parameters and representation. It uses probability distributions as parameters to model demand and lead time uncertainty, and formulates service level constraints as linear inequalities. This parameter transformation enables accurate handling of nonstandard demand distributions and multiple service level targets while maintaining computational tractability through linear programming techniques.
2Reliability
If inventory policies are optimized for multiple service level targets, then service level compliance is improved, but computational difficulty increases
Solution Approach 1:
The patent introduces linear programming as an intermediary computational framework that mediates between the complex requirements of multiple service level targets and the need for tractable computation. By formulating the inventory optimization problem as a linear program with probability distribution parameters, it creates an intermediate mathematical representation that can handle multiple service level constraints systematically. This intermediary formulation allows the use of efficient linear programming algorithms to find optimal policies that comply with multiple service level targets.
3Adaptability or versatility
If demand distributions are made nonstandard to reflect real-world variability, then realism of model is improved, but solvability of optimization problem deteriorates
Solution Approach 1:
The patent substitutes traditional mechanical optimization approaches with a linear programming framework that is better suited for handling nonstandard probability distributions. Instead of relying on closed-form solutions or standard optimization techniques that assume normal or simple demand distributions, it replaces the mechanical solution method with a linear programming approach that can accommodate arbitrary probability distributions. This substitution maintains ease of solving by leveraging the well-developed theory and algorithms of linear programming.
Data Source
AI summary
A system and method are disclosed for an inventory planner that generates an inventory policy using any form of demand distributions, non-linear cost functions and/or multiple target measures of service levels, while taking into account a supply order lead time, such as, for example, a static or stochastic supply order lead time. The inventory policy generated by the inventory planner comprises an optimal and reproducible solution to one or more supply chain planning problems.