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Solutions for Airlines

Few industries operate under constraints as demanding as airlines—characterized by high resource costs, largely fixed operating expenses regardless of demand, the perishability of inventory, and the inherent complexity of network-based operations. Our work in the airline domain has consistently shown that optimal and agile decision-making, powered by data-driven analytical models, can significantly influence performance in an industry known for its wafer-thin margins.

 

At OPTIVARA, we apply deep expertise in Operations Research and Data Science to build advanced optimization solutions across Network Planning, Revenue Management, Disruption Recovery, Maintenance and Tail Assignment Planning, and Ground-Staff Resource Planning & Rostering. Our solutions enable airline leaders to evaluate scenarios and generate optimal decisions within minutes—while adhering to the diverse strategic and operational constraints that define modern airline operations.

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Network Planning

Clean-Sheet Network Designer

OPTIVARA's Network Designer allows Airline Network Planners to evaluate multiple scenarios such as additional of a new city, new route, new frequency of an existing route, re-time of existing flights, airport curfews, maintenance slots requirements, etc. and rebuild the revenue maximizing rotated schedule. Our algorithm not only evaluates the best routes and best times to operate a flight using customer-choice model  but also ensures that these flights form a feasible rotated schedule.

Revenue Management

Inventory and Pricing Optimization

Our AI-powered algorithm combines demand forecasting, optimal inventory control, competitor response strategy, and demand-influencers to generate the optimal fare-offer. The pricing optimizer module allows airlines to design optimal fare-ladder based on willingness-to-pay, competitor fare levels, and seasonality. Our algorithm can even generate optimal Network or O&D inventory controls for LCC-native reservation systems.

Financial Reports
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Operations Control Center

Multi-criteria Disruption Recovery Manager

OPTIVARA's Disruption Recovery Manager can generate multiple disruption recovery plans simultaneously with different objectives (financial, customer, operational) thereby allowing operations controllers to select the recovery plan that best meets the business objectives and the disruption situation. The recovery plan not only encompasses recommendations on flights to delay / cancel but also rebuilt aircraft routing, maintenance schedules, as well as alternate itineraries of disrupted pax in order of their loyalty-tier or fare class.

Engineering & Ops Control Center

Maintenance and Tail-Assignment Planner

Airline Maintenance and Operations Control Center Teams are often confronted with the challenge of deciding when and where to schedule maintenance checks for each tail such that all maintenance due-date requirements are honored, entire flight schedule is covered, and the operating cost is minimized. OPTIVARA's dual-objective Maintenance and Tail-Assignment Planner builds maintenance plan and tail-routings thereby concurrently optimizing the maintenance schedule and the operating costs.

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Airport Baggage Handling

Ground Operations

Workforce Planning and Rostering

The biggest challenge in ground workforce planning for airlines is the variability of workload throughout the day depending on the flights schedule during peak and non-peak hours. A sub-optimal planning can lead to either excess workforce during lean-operation hours of the day resulting in higher costs, or shortfall during peak-operation hours resulting in delays and impact on service standards. OPTIVARA's Workforce Planning & Rostering solution maps workload by each activity and determines the optimal staff shift plans to cover the variable workload. Accordingly the rostering plan is developed keeping in mind workforce unavailability due to weekly-offs, planned leaves, trainings, and unplanned leaves. The roster then feeds into task-assignment module which lays out the assignments to different tasks for each individual in each shift.

 

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