Guide
Getting Started
SSPLAX is a decision engine for constrained systems. You describe a system — what flows through it, what limits apply, and what you want to optimize — and the solver returns the best feasible plan along with the constraints that shaped it.
How SSPLAX works
SSPLAX turns a system of flows, limits, and goals into a clear decision. You define what can move, what constrains it, and what outcome matters most.
SSPLAX solves for the best feasible plan, then explains which limits shaped the answer, which assumptions matter most, and which changes would move the decision.
The core loop
Every SSPLAX session follows the same pattern:
Pick a starter template for your domain or build a flow network from scratch. The model defines what moves through your system and how stages connect.
Tell SSPLAX what you want: maximize throughput, minimize cost, or minimize resource consumption. If there are minimum delivery requirements, set those too.
Set capacity limits, budgets, yield ratios, and cost rates. Each constraint reflects a real-world limit. Mark your confidence level and range for each one.
The solver returns the optimal plan, active limits, bottlenecks, marginal values, and available headroom. You see which limits are shaping the answer and what relaxing each one would buy you.
Change assumptions, compare scenarios side by side, run sensitivity analysis, and test hypotheses. Promote the best scenario to your new baseline and build a decision brief.
Your first model in five minutes
The fastest way to learn SSPLAX is to open an example and change something.
- 1. Go to Examples and open any scenario — Engineering Capacity is a good one to start with.
- 2. Click Open this model. You'll land in the workspace with the template loaded.
- 3. Pick an objective and proceed to the Constraints screen.
- 4. Drag a constraint slider — say, tighten a budget or lower a capacity limit — and hit Solve.
- 5. The Results screen shows the optimal plan and highlights what changed. Look for amber active-limit labels — those are your bottlenecks.
That's it. You've just run a constrained optimization, identified the active limits, and seen how the recommendation shifts when assumptions change. The rest of this guide goes deeper into each step.
Key concepts
These terms appear throughout SSPLAX. For full definitions, see the Glossary.
A stage in your system — a source, service, queue, or sink. Nodes are connected by edges.
A flow path between two nodes. Each edge carries a commodity (like throughput) with min/max bounds, cost, yield, and optional resource consumption.
A limit on the system: a budget cap, capacity ceiling, minimum delivery requirement, or resource limit. Constraints are what make the problem interesting.
What you want to optimize — maximize throughput, minimize cost, or minimize resource use.
A constraint that is fully used in the recommended plan. Solver notes may call this a binding constraint. Relaxing an active limit can improve the answer.
How much the objective improves when you relax a limit by one unit. Solver notes may call this shadow price. A high marginal value means the limit is worth investigating.
How much room is left before a limit becomes active. Solver notes may call this slack. More headroom usually means that constraint is not driving the decision.