Choosing the Right Optimization Goal
Understand the five optimization goals available in Formict and when to use each one.
Formict offers five optimization goals, each designed for different operational priorities. Every goal is available on all plans — choose based on your business needs, not your subscription tier.
Minimize Distance
Best for: Reducing fuel costs and vehicle wear.
The solver finds routes that cover the least total distance across all vehicles. This is the default goal and works well for most field service operations.
Trade-off: Some vehicles may end up with significantly more stops than others.
Minimize Time
Best for: Completing all jobs as early as possible.
Instead of distance, the solver minimizes total travel and service time. This accounts for traffic patterns and variable service durations.
Trade-off: May use more fuel by choosing faster but longer routes.
Minimize Cost
Best for: Fleet operations with diverse vehicle costs.
Uses your configured fixedCost, costPerKm, and costPerHour per vehicle. The solver might leave expensive vehicles idle if cheaper ones can handle the load.
Trade-off: Requires accurate cost data to be effective.
Balance Workload
Best for: Keeping team utilization fair while still optimizing.
The solver minimizes distance as the primary goal but adds a secondary constraint to distribute jobs more evenly across vehicles.
Trade-off: Total distance may be 5–10% higher than pure distance minimization.
Split Equally
Best for: Union environments or strict fairness requirements.
Distributes jobs as equally as possible across vehicles. Each vehicle gets within ±1 job of the average.
Trade-off: Total distance may be 10–20% higher. The solver prioritizes fairness over efficiency.
Decision Matrix
| Priority | Goal |
|---|---|
| Lowest fuel cost | Minimize Distance |
| Fastest completion | Minimize Time |
| Lowest total cost | Minimize Cost |
| Fair + efficient | Balance Workload |
| Strict fairness | Split Equally |
All five goals respect your hard constraints: time windows, capacity limits, skill requirements, and break schedules. The goal only changes how the solver optimizes within those constraints.