Planning Applications
Better plans for changing operations
Takt, Roster and Stride bring optimization to production, shift and project planning. When priorities change, each re-plans within your rules.
An AI assistant sets each one up with you, and you explore scenarios before you commit.
One app for each planning problem
Each app starts from your own data and rules, and re-plans when the day changes.
When the day changes, the plan follows
Each app re-plans the whole picture when something changes, not just the next free slot.
A sequence planned as a whole
Takt groups jobs to cut changeovers and plans the whole sequence at once, so the same machines finish the day's work sooner.
Later, ask the assistant what-if questions: change the order of orders, add a rush job or take a machine offline, and compare the revised schedules.
Discover TaktTen jobs, three machines, three product families. Changeovers (red) cost time.
All jobs done after13 h
Changeovers3
Illustrative example, not customer data.
A sick call, covered within your rules
When someone calls in sick, Roster re-plans the week within your working rules, so every shift stays covered with the right skills.
Later, ask the assistant what-if questions: who covers if a specialist is absent, what changes if demand shifts, and which assignments move.
Discover RosterA week for six people: early (teal) and late (blue) shifts.
Uncovered shifts0
Shifts changed0
Illustrative example, not customer data.
One slip, every project re-planned
When one project slips, Stride re-plans every project that shares its teams, so the delay does not quietly cost another milestone.
Later, ask the assistant what-if questions: move a milestone, shift a deadline or lose a team for a week, and see which commitments are at risk.
Discover StrideTwo projects, A (teal) and B (blue), share three teams. Project A's design work takes two days longer.
Milestones met2 of 2
Project B finishesDay 8
Illustrative example, not customer data.
Your data, your planning decisions
Bring planning data from your business systems into one workflow. An AI assistant helps configure the rules and priorities, while your team reviews the model and chooses the plan.
Scenario analysis:
Ask what happens when demand changes, a resource becomes unavailable or a deadline moves. Compare the alternatives against your operating objectives.
Fast reoptimization:
When a disruption changes the plan, search for a practical new schedule without starting the planning process from scratch.
Planning confidence:
Explore capacity, tradeoffs and feasible options before making a commitment.
Under the hood
Planning applications run on the 4colors Optimizer
Takt, Roster and Stride run on 4colors optimization algorithms, the family that set new best-known schedules on a public project-scheduling benchmark.
Rules you describe become a model the engine searches within your time budget, so what-if questions return comparable alternatives, not a single plan.
Powered by
4colors Optimizer
Original search algorithms, tested on demanding benchmarks and run to your time budget. Also powers the Optimizer for Scheduling, the Optimizer for QUBO and the Quantum Compiler.
Explore the 4colors OptimizerBuilding scheduling into your software?
4colors Optimizer for Scheduling brings high-performance scheduling algorithms into developer workflows. For problems that combine scheduling, routing and loading, explore Custom Optimization.
Three planning problems, three different models
Explore more use cases- Use case
Why Scheduling a Factory Is Harder Than Lining Up the Jobs
A factory contains several clocks, and they do not always agree. A machine becomes free just as the necessary operator goes off shift.
Explore the use case - Use case
The Mathematics of a Fair and Workable Roster
Two schedules can cover every shift and still create very different weeks for the people working them.
Explore the use case - Use case
The Project Plan That Cannot Happen
Even a flawless dependency chart can promise work that the team has no capacity to perform.
Explore the use case - Guide
Build a Small Workforce Roster Model
A small staffing example reveals the difference between assigning shifts and modeling a fair schedule.
Read the guide - Insight
A Good Production Schedule Is More Than a Gantt Chart
The bars show when work happens. The difficult questions are why it happens in that order, and what changing the order would cost.
Read the insight - Insight
Which rules can bend?
Every optimization model draws a line between what must be true and what would be preferable. That distinction shapes every answer.
Read the insight
Explore planning with 4colors
Bring a real week of planning data, and see what an optimized plan does with it.