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The Impact of Disruptions

Studies have estimated that irregular operations can cost between 2% and 3% of the airline annual revenue and that a better recovery process could result in cost reductions of at least 20% of its irregular operations.

 

Millions of Flights Delayed

Millions of Passengers Delayed.

Millions of Euros in Costs of Delayed Flights
* Data for Europe only in 2014

 

 

The traditional sequential approach
leads to an unbalanced solution

Typically, the Airline Operations Control Centers (AOC)
as well as the current solutions proposed by others,
follow a sequential approach which imposes a natural order of importance
leading to an unbalanced solution.

 

Why the traditional approach doesn’t work…

 

1

A Disruption happens

Aircraft malfunction, weather, air traffic control and late arrival of incoming aircraft are among the most common causes of disruption.

 

2

Solve the aircraft part

A suitable aircraft is found and assigned to the delayed flight.

 

3

Solve the crew part

Considering the previously chosen aircraft, a qualifed crew is found and assigned to the delayed flight.

 

4

Solve the Passenger part

Considering the estimated flight depature delay caused by the chosen aircraft and crew, passengers are reaccommodated accordingly.

 

5

Unbalanced Solution

A natural order of importance is imposed, making the passenger part less important than the crew and aircraft parts.
This might result in loss of passenger goodwill and sub-optimal cost solution.

 

sequential_retina2

Goal Achievement of a Traditional Approach

Each part of the problem has different goals:
The Aircraft and Crew part minimize direct costs; the Passenger part minimize the direct costs and increase passenger goodwill.
The global perspective wants to balance the goals of the three previous parts.

 

90%

Aircraft Part

80%

Crew Part

60%

Passenger Part

73%

Global

The multi-agent model driven solution

We use the Multi-Agent System (MAS) paradigm to represent the roles that exist in the AOC
combined with advanced distributed artificial intelligence techniques.

 

Software Agents

A software agent represents each part of the problem including its preference and goals: aircraft, crew and passenger. Another software agent represents the global view of the airline company.

Automated Negotiation and Learning

Through an automated negotiation process, called Generic Q-Negotiation (GQN),  the best integrated solution is chosen according to the global interest of the airline. 

Intelligent Decision Making

This results in an autonomous, automated and adaptative system that also includes the human agent in the decision process. Human factors are very important.

MASDIMA core features and benefits

Operational Plan Monitoring

In a 3D visual display the operational plan is monitored in real-time allowing to track flights.

 

 

Integrated Problem Solving

The best integrated solution is found including a solution for the aircraft part, a solution for each of the crew members, and for each passenger, including crew and passenger reaccommodation.

 

Apply Solution to Operational Plan

After human approval, the operational plan is updated accordingly including passenger rebooking.

Event Detection

Events like: aircraft malfunction, weather and ATC restrictions, crew problems, passenger and baggage delay, among others are detected in real-time.

 

Human in The Loop

Human factors are important. All candidate solutions are presented to the human for feedback and/or approval.

 

Simulation

MASDIMA is able to run with past or future data, allowing to perform what-if scenarios either with historical events and/or simulated events accordingly to a specific model.

Disruption Impact Assessment

The impact of a disruptive event is assessed in the operational plan of the aircraft, considering all affected crew members and passengers (including missed connections).

 

Passenger Interaction

A customer-centric view in IROPS is important. Passengers have the possibility to interact with the system so that the solution is aligned with the passenger preferences.

 

Improve Future Plans

MASDIMA can execute an not yet released operational plan, simulating future events and allowing to improve the plan using the simulation results.

Goal Achievement of Our Approach

Our approach allows to achieve a balanced integrated solution.
This means that each part improves each own goals and at the same time improving the global objective.

 

95%

Aircraft Part

90%

Crew Part

95%

Passenger Part

93%

Global

Real data simulated experiments show that MASDIMA has the possibility of reducing the cost with IROPS between 13% to 48%, reduce by 86% the flight delays and increase the passenger satisfaction by 58% (on average)

Suitable for all means of transport

If your business is getting passengers or cargo from point A to point B, our solution is transport mean-independent.
Either by air, land or sea, MASDIMA can help you overcome disruptions in the most intelligent cost-effective way.

Aviation

Rail

Public Transport

Logistics

Meet our team

We believe in a multidisciplinary team who has been dealing in the resolution of real-world problems in the areas of artificial intelligence, airline operations and large scale information systems management in the past 30 years.

FIND OUT MORE ABOUT US

 

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Address

MASDIMA, Lda.
UPTEC – Science and Technology Park of University of Porto
Rua Alfredo Allen
N.º 455/461, 4200-135
Porto,Portugal

Contact details

Email: info@masdima.com

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