Supply Chain Optimization
& Simulation

Free Supply Chain Optimization & Simulation Tool (LP/NLP Solver)

A free linear and non-linear programming solver for production planning, transportation and procurement — define your objective and constraints, and optimise across up to 50 SKUs entirely in your browser.

What is supply chain optimization?

Supply chain optimization uses mathematical programming to find the best decision — lowest cost, highest profit, shortest distance — subject to real-world constraints like capacity, demand and budget. Where a spreadsheet can only test a few scenarios, an optimiser searches the entire feasible space and returns the provably best answer. This tool supports both linear (LP) and non-linear (NLP) problems.

What problems can it solve?

• Production planning — allocate output across products and lines to maximise throughput or margin.
• Transportation — assign shipments to routes and modes to minimise cost or distance.
• Procurement — split orders across suppliers under price, capacity and risk constraints.

LP vs NLP — what's the difference?

Linear programming assumes cost and benefit scale proportionally — doubling volume doubles cost. Non-linear programming handles real-world effects like economies of scale, quantity discounts and diminishing returns, where the relationship curves. This tool lets you model both, so the answer reflects how your costs actually behave.

Who is this optimisation tool for?

Supply chain planners, operations researchers, procurement managers and students who want hands-on optimisation without installing solvers or writing code. For production-scale, multi-thousand-SKU optimisation, Mathnal builds custom engines — this free tool demonstrates the methodology.