Price Optimization Using Business Rule Penalty Values
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Solution Overview
Problem
Existing retail price optimization techniques often generate recommended prices that conflict with business rules, leading to sub-optimal solutions as they treat business rules as either absolute constraints or post-process procedures, making it difficult to balance revenue, profit, and rule compliance.
Innovation Solution
A price optimization technique that assigns a monetary value to each business rule, optimizing revenue and profit while ensuring compliance with business rules by generating constrained and unconstrained best solution sets using revenue-profit weights and penalty values to determine the best price sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If business rules are treated as absolute constraints in price optimization, then rule compliance is improved, but revenue and profit optimization deteriorates
Solution Approach 1:
The patent transforms business rules from absolute constraints into parameterized constraints with associated penalty values. Each business rule is assigned a monetary penalty value that quantifies the cost of violation, allowing the optimization algorithm to balance rule compliance against revenue and profit maximization. This parameterization enables flexible trade-offs where the system can selectively violate low-penalty rules to achieve higher overall profitability while maintaining compliance with high-penalty critical rules.
2Productivity
If business rules are treated as post-process procedures, then revenue and profit optimization is improved, but rule compliance deteriorates
Solution Approach 1:
The patent incorporates business rule compliance checks and penalty assessments into the price optimization process itself, rather than applying them as post-processing steps. The penalty values for rule violations are integrated into the objective function during optimization, allowing the system to proactively identify and adjust prices that would violate business rules before final recommendations are generated. This preliminary integration ensures both revenue optimization and rule compliance are achieved simultaneously.
3Reliability
If multiple business rules are applied to product networks, then rule compliance quality is improved, but solution complexity deteriorates
Solution Approach 1:
The patent merges multiple business rules into a unified optimization framework where all rules are represented as parameterized constraints with penalty values. Instead of handling each business rule separately through multiple processing steps, the system combines them into a single objective function that simultaneously considers revenue, profit, and all applicable business rules. This merging reduces solution complexity by consolidating what would otherwise require sequential rule-checking and adjustment processes into one integrated optimization calculation.
Data Source
AI summary
The disclosed technology improves the process of generating recommended prices for retail products by optimizing revenue and profit while complying with a set of business rules by assigning a monetary value to each business rule. Then for each decision price that violates a business rule constraint, a penalty value is added to the monetary value. If the monetary value including the penalty is better than an original monetary value, the decision price is included in the recommended prices.


