Step 03 · Optimization Engine
On the roadmapWhat should we do?
Cheapest replenishment and loading plan that keeps depot service above 97%.
Solver output: how much of each SKU moves to which depot, on which truck, on which day, under real vehicle, warehouse and empties-pool constraints.
−11% freight cost
Service ≥ 97%
Terms on this page
- Depot service
- The share of orders a depot fills from stock.
- Empties pool
- The returnable bottles and crates collected from the market for refilling.
- Solver
- An optimization algorithm that finds the best plan satisfying every constraint.
How the Optimization Engine gets there
- 01The same proprietary agentic structure as prediction, applied to prescriptive questions, starting from forecasts the Prediction Engine already produced.
- 02The agent translates the business problem into a formal model: decision variables, constraints, and an objective.
- 03Exact methods (linear and mixed-integer programming solvers) run where provable optimality is achievable.
- 04Heuristics and metaheuristics take over where problem scale demands fast, high-quality approximate solutions.
On the roadmap. Turns Prediction Engine output into constrained, actionable decisions.
Explore the Optimization EngineWhat changes
The relay today
The relay often never starts. OR talent is rationed to a handful of flagship projects.
With Theovya
Solver-grade decisions on every planning question, not just the six-month engagements.
The same three questions every distribution business asks. The difference is that here they are asked by the same person, on the same afternoon.