What is the Inventory & Demand multi-solver?

Inventory & Demand is a guided workflow that chains 2 individual PolySim solvers into one end-to-end analysis, piping each result into the next step.

Yes. Every step runs entirely in your browser using real numerics — no install, no account, no cloud cost. Custom or private solver packs are available as a paid service.

Operations & Economics Pack · Multi-Solver

Inventory & Demand

Forecast & safety stock. This multi-solver chains 2 solvers into a single guided workflow — run each step in order and carry the result forward.

Workflow steps

eoq
→monte-carlo

or unlock everything with Pro →

Eoq

open full solver →

Economic Order QuantityLive

the inventory sweet spot

Controls

Presets

Annual demand D

Cost per order S ($)

Holding cost H ($/unit/yr)

Order too often and ordering costs pile up; order too much and holding costs balloon. The Economic Order Quantity, EOQ = √(2DS/H), is the order size that minimizes their sum. At the optimum the ordering and holding costs are exactly equal — the crossing point of the two curves. The foundation of inventory management.

▶ Run in Python

Data Inspector

EOQ707 units

Orders / year14.1

Min total cost$1414

Governing equation

Q^{*} = \frac{2 D S}{H} = \frac{2 \cdot 10000 \cdot 50}{2} = 707

Reading this result: At the EOQ the two curves cross: yearly ordering cost equals yearly holding cost, giving about 14.1 orders a year at the minimum total cost.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

↓

Monte Carlo

open full solver →

Monte Carlo Price SimulationLive

geometric Brownian motion

Controls

Presets

Initial price S₀

Expected return μ

Volatility σ

Horizon (years)

Geometric Brownian motion models a price with constant drift and random volatility — the assumption behind Black-Scholes. Running hundreds of simulated paths reveals the full distribution of outcomes, not just an average. Educational tool, not investment advice.

▶ Run in Python

Data Inspector

Median outcome$0

5th percentile$0

95th percentile$0

Governing equation

S_{t + Δ t} = S_{t} e^{(0.07 - \frac{0. 2 ^{2}}{2}) Δ t + 0.2 Δ t Z}, \tilde{S}_{1} \approx $0

Reading this result: Median outcome is about $0, just under the drift-only $107 — GBM compounds in log-space, so volatility always pulls the typical path below the average.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

Need a private, branded version?

We build custom solvers and workflows for labs, firms, agencies, and courses — your parameters, your branding, your data.

Explore Custom Solver Sets →

More in the Operations & Economics pack

Supply-Chain Optimizer Facility Location Project Portfolio Market Equilibrium Lab Auction Designer Pricing Strategy Network Reliability Traffic Flow Planner

Frequently asked questions

What is the Inventory & Demand multi-solver?: Inventory & Demand is a guided workflow that chains 2 individual PolySim solvers into one end-to-end analysis, piping each result into the next step.
Is it free to use?: Yes. Every step runs entirely in your browser using real numerics — no install, no account, no cloud cost. Custom or private solver packs are available as a paid service.