Demand Forecasting and Inventory Optimization Through Stochastic Simulation
SoPlenty classifies demand patterns, generates probabilistic forecasts, and computes time-varying reorder policies optimized across 100 simulated demand scenarios. Service level and inventory objectives are set directly — no financial costing required.
Classification-Driven Forecasting
7 demand types. 29 benchmarked models. Each item is routed to the best-performing method by rolling cross-validation on actual data.
Stochastic Simulation
The Seeker solver optimizes reorder policies across the full distribution of demand scenarios simultaneously — not against a point forecast. Policies are found through uncertainty, not tested against it after the fact.
Multi-Objective Optimization
Service level and inventory targets are set directly as min and excellent objectives. No cost of goods sold, no selling price, no imputed cost of a stockout. The system reports when targets cross the efficient frontier.
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