Aviation | Optimization | Consulting
Empowering smart decisions in aviation & beyond.
We develop decision-support systems to ensure efficient, safe and sustainable transport operations.
What We Offer
The transportation industry is full of operational challenges and complex day-to-day decisions.
At Wing Labs, we believe that a functioning Advanced Analytics toolset is therefore indispensable.
As a consulting and software development company specialising on (air) transportation, we take your decision-support tools to the next level.
Customized decision-support tools
Our programming experts develop, validate, test and implement Advanced Analytics & Data Science tools tailored to your problems.
Flexible project & modeling support
If you already have a clear view what you need, you can benefit from our modeling expertise through flexible project support.
Our industry expertise spans all important players across the aviation landscape.
Air Traffic Management
Airports & Infrastructure
Transport & Logistics
Network planning decisions are strategic in nature and therefore subject to substantial uncertainties. Simulation and optimization tools can help make better decisions and increase expected revenues.
Applications: Airline network planning (Airlines), Network Operations Plan development (ATM)
Transport Optimization & Routing
With rising fuel prices, choosing the most fuel-efficient route is key. Optimization can help choose the right trajectories given a wide range of constraints.
Applications: Route planning (Airlines, Logistics), strategic operations and special event planning (ATM)
Pricing & Revenue Management
Dynamic pricing has revolutionised the way airlines and hospitality companies think about sales. Adjusting prices based on expected demand and actual capacity can substantially increase revenues.
Applications: Airfare optimization (Airlines), airport slot allocation (Airports), airspace charging (ATM)
Similar to network planning decision, capacity decisions are strategic and have long-lasting impact. Using simulation to model various scenarios from the start can help reduce the impact of unexpected events.
Applications: Fleet optimization (Airlines), Runway capacity planning (Airports), Airspace capacity planning (ATM)
Resource Allocation & Scheduling
Aviation players handle scarce and expensive resources on a daily basis. Deciding on the most beneficial allocation of planes, pilots, slots and gates is a constant challenge, with large upside potential.
Applications: Tail assignment (Airlines), Crew scheduling (Airlines), Slot allocation (Airports), Air Traffic Controller rostering (ATM)
Demand Modeling & Forecasting
The last years have shown how vulnerable existing systems are to volatility in demand. Generating reliable forecasts serves as a basis for effective business, network and capacity planning.
Applications: Passenger forecasts (Airlines), Flight forecasts (Airports), Air traffic forecasts (ATM)
We possess functional expertise in simulation, optimization and machine learning to design the Advanced Analytics tools you need.
Mathematical Optimization, also known as Mathematical Programming, involves the process of finding the optimal solution for a given problem by mathematically formulating it and employing specialized algorithms. It aims to maximize or minimize an objective function while satisfying a set of constraints. By systematically exploring various possibilities, mathematical optimization enables us to make informed decisions and achieve optimal outcomes in fields like finance, engineering and logistics.
In aviation, optimization techniques help allocate airport slots, plan airline routes or schedule aircraft maintenance.
Monte Carlo Simulation
Monte Carlo Simulation is a computational technique used to estimate and analyze the behavior of complex systems or processes by simulating random variables. It involves repeatedly generating random samples and using them to evaluate various scenarios. By running numerous iterations, patterns and trends can be identified. It is a powerful tool to make informed decisions in situations involving uncertainty, enabling us to understand the range of possible outcomes and take appropriate action.
In aviation, we can apply simulation to assess the impact of different arrival/departure procedures at airports to improve flight sequences and runway capacity utilisation.
Machine Learning is a branch of artificial intelligence that focuses on developing algorithms and models capable of learning from data and making predictions or decisions without being explicitly programmed. It involves training a system with historical data to identify patterns, relationships, and trends, enabling it to make accurate predictions or classifications.
In the aviation industry, machine learning can be employed in predictive maintenance, where algorithms analyze sensor data to detect anomalies and predict component failures.
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