Constraint-Driven Aircraft Assignment
Build workable schedules that follow the rules used in daily operations.
- Minimum turnaround time
- Station continuity
- Fleet and aircraft compatibility
- Availability windows and service periods
Constraint-aware aircraft scheduling
Optimize aircraft schedules around real operations
Build workable aircraft schedules around maintenance requirements, fleet compatibility, station continuity, and airline-specific rules. Use the Genetic Algorithm or Pathy to match the optimization approach to the problem.
Constraint-aware
Build schedules around real operating limits from the start.
Scenario-driven
Compare several options and understand their costs and tradeoffs.
Integration-ready
Connect cloud-based scheduling with your other systems.
Genetic Algorithm example
Evolutionary search over successive generations
The Genetic Algorithm explores many complete schedules and improves them through successive generations.
Illustrative trace — not customer or production data. OFR = Onward Flight Reference.
Two optimization engines. One operational objective.
Choose the optimization approach that best fits the scenario: broad evolutionary exploration with the Genetic Algorithm or structured, path-based coordination with Pathy. Both apply the same operational constraints and cost framework.
Genetic Algorithm
The Genetic Algorithm uses an evolutionary search to explore many complete scheduling alternatives. Over successive generations, it combines and improves solutions across a large and complex search space.
- Evolutionary optimization
- Broad exploration across complete schedules
- Continuous improvement over successive generations
Pathy
Pathy is a path-based optimization algorithm developed specifically for complex aircraft assignment and recovery scenarios. It uses column generation to expand relevant operational alternatives and coordinate aircraft paths across the complete schedule.
- Builds feasible operational paths
- Expands the available choices
- Coordinates the complete solution
Built for real airline operations
OptCo does more than match aircraft to flights. It includes maintenance needs, operating policies, and assignment rules so the schedule fits how the airline works.
Rules Matrix
Let planners define which activity-resource matches should be preferred, non-preferred, or forbidden.
- Direct control over assignment logic
- Airline policies included in the optimization
- Reports that show the effect of each rule
- More detail than a simple compatibility check
Maintenance Routing with Station Capabilities
Route aircraft to stations that can perform the required maintenance and have capacity available.
- Station capabilities
- Available station capacity
- Aircraft maintenance requirements
- Maintenance built into the operating plan
Multi-Leg Flight Integrity
Keep linked activities together when they must operate as one unit.
- Keeps grouped activities intact
- Prevents broken operating sequences
- Supports real flight groupings
Scenario Comparison & Cost Transparency
Compare schedules side by side and understand why one scenario performs better than another.
- Cost breakdown per leg
- Cost breakdown per aircraft
- Total scenario comparison
- Clear view of tradeoffs and results
Optimization Guided by Your Operation
Optimize schedules using the airline’s own priorities and constraints.
- What-if comparisons across scenarios
- Measurable tradeoffs
- Room to add more operating rules
Aircraft scheduling, explained
See how OptCo handles the main decisions behind a workable aircraft schedule.
Aircraft Scheduling Optimization
See how two optimization engines bring assignments, constraints, maintenance requirements, policy, and scenario costs together.
Explore the optimization engines →Aircraft Tail Assignment
Assign individual aircraft while checking timing, location, compatibility, and availability.
Explore tail assignment →Maintenance Routing
Connect aircraft maintenance needs with station capability, capacity, and the operating rotation.
Explore maintenance routing →Assignment Rules Matrix
Include preferred, non-preferred, and forbidden matches in the search.
Explore assignment rules →Results you can measure
A good schedule must do more than work. Planners should also be able to understand it, compare it, and trust it.
Higher aircraft utilization
Use the fleet more effectively while staying within operating limits.
Faster schedule creation
Reduce manual scheduling effort and generate stronger candidate schedules faster.
Greater planner trust
Show schedule quality through clear reports, scenario comparisons, and costs.
Better operational control
Use configurable airline rules instead of one-size-fits-all logic.
Designed to work with airline systems
OptCo supports airline workflows, secure data exchange, and automatic delivery of results to connected systems.
Integration & deployment
Run OptCo in the cloud and send results automatically to other systems through configurable interfaces.
AWS cloud based
Automated exports
API-driven exchange
Interface ready
- Secure import of operational scheduling inputs
- Automated export of schedule outputs and scenario results
- Connections to airline planning and operational systems
- Flexible support for new workflows and systems
Built by people who know airline operations
The OptCo team has hands-on airline experience and has worked directly with real scheduling and optimization problems.
Domain understanding
The founding team combines experience in airline operations systems with practical optimization work.
Product vision
Our goal is simple: build a powerful scheduling tool that planners can understand and use in real operations.
More about OptCo →Interested in seeing OptCo in action?
Request a demo to see how OptCo can support your scheduling process, compare options, and make tradeoffs easier to understand.