{"id":7606,"date":"2013-03-09T05:01:39","date_gmt":"2013-03-09T05:01:39","guid":{"rendered":"http:\/\/themes.swiftpsd.com\/test\/flexform\/?page_id=7606"},"modified":"2024-02-13T17:07:28","modified_gmt":"2024-02-13T17:07:28","slug":"home","status":"publish","type":"page","link":"http:\/\/masdima.pt\/home\/","title":{"rendered":"MASDIMA Home"},"content":{"rendered":"[blank_spacer height=”70px” width=”1\/1″ el_position=”first last”] [spb_single_image image=”12548″ image_size=”full” frame=”noframe” intro_animation=”none” full_width=”no” lightbox=”no” image_link=”https:\/\/upin.up.pt\/pt-pt\/content\/spin-offs-uporto” link_target=”_blank” width=”1\/6″ el_position=”first”] [blank_spacer height=”2px” width=”1\/4″] [spb_single_image image=”12545″ image_size=”full” frame=”noframe” intro_animation=”none” full_width=”no” lightbox=”no” image_link=”https:\/\/sigarra.up.pt\/feup\/en\/web_base.gera_pagina?p_pagina=spin-offs%20feup” link_target=”_blank” width=”1\/6″] [blank_spacer height=”2px” width=”1\/4″] [spb_single_image image=”12713″ image_size=”full” frame=”noframe” intro_animation=”none” full_width=”no” lightbox=”no” image_link=”https:\/\/liacc.fe.up.pt\/” link_target=”_blank” width=”1\/6″ el_position=”last”] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/1″ el_position=”first last”]\n

The Impact of Disruptions<\/span><\/p>\n

Recent studies have estimated that irregular operations can cost up to 6% of the airline annual revenue and that a better recovery process could result in cost reductions of at least 20% of its irregular operations.<\/h3>\n

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Millions of Flights Delayed<\/h6><\/div>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” el_class=”mt0 pt0″ width=”1\/3″]\n

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Millions of Passengers Delayed.<\/h6><\/div>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” el_class=”mt0 pt0″ width=”1\/3″ el_position=”last”]\n

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Millions of Euros in Costs of Delayed Flights<\/h6><\/div>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/1″ el_position=”first last”]\n
* Data for Europe only in 2018\u00a0<\/span><\/h6>\n

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 <\/p>\n

The traditional sequential approach<\/span>
\nleads to an unbalanced solution<\/span><\/p>\n

Typically, the Airline Operations Control Centers (AOC)<\/span>
\nas well as the current solutions\u00a0proposed by others,<\/span>
\n follow a sequential approach which imposes a natural order of importance<\/span>
\nleading to an unbalanced solution.<\/span><\/h3>\n

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Why the traditional approach doesn’t work…<\/span><\/p>\n

 <\/p>\n

1<\/span><\/div>

A Disruption happens<\/h3>

\nAircraft malfunction, weather, air traffic control and\u00a0late arrival of incoming aircraft are among the most common causes of disruption.
\n<\/div><\/div><\/div>\n

 <\/p>\n

2<\/span><\/div>

Solve the aircraft part<\/h3>

\nA suitable aircraft is found and assigned to the delayed flight.
\n<\/div><\/div><\/div>\n

 <\/p>\n

3<\/span><\/div>

Solve the crew part<\/h3>

\nConsidering the previously chosen aircraft, a qualifed crew is found and assigned to the delayed flight.
\n<\/div><\/div><\/div>\n

 <\/p>\n

4<\/span><\/div>

Solve the Passenger part<\/h3>

\nConsidering the estimated flight depature delay caused by the chosen aircraft and crew, passengers are reaccommodated accordingly.
\n<\/div><\/div><\/div>\n

 <\/p>\n

5<\/span><\/div>

Unbalanced Solution<\/h3>

\nA\u00a0natural order of importance is imposed,\u00a0making the passenger part less important than the crew and aircraft parts.
\nThis might result in loss of passenger goodwill and sub-optimal cost solution.
\n<\/div><\/div><\/div>\n

 <\/p>\n[\/spb_text_block] [spb_single_image image=”12199″ image_size=”full” frame=”noframe” intro_animation=”fade-from-right” full_width=”no” lightbox=”no” link_target=”_self” el_class=”visible-lg” width=”1\/2″ el_position=”last”] [blank_spacer height=”86px” el_class=”visible-lg” width=”1\/1″ el_position=”first last”] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/1″ el_position=”first last”]\n

Goal Achievement of a Traditional Approach<\/span><\/p>\n

Each part of the problem has different goals:
\nThe Aircraft and Crew part minimize direct costs; the Passenger part minimize the direct costs and increase passenger goodwill.
\nThe global perspective wants to balance the goals of the three previous parts.<\/h3>\n

 <\/p>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/1″ el_position=”first last”]\n

\n
90%<\/span><\/div>\n

<\/div>\n

Aircraft Part<\/h4>\n<\/div>\n
\n
80%<\/span><\/div>\n

<\/div>\n

Crew Part<\/h4>\n<\/div>\n
\n
60%<\/span><\/div>\n

<\/div>\n

Passenger Part<\/h4>\n<\/div>\n
\n
73%<\/span><\/div>\n

<\/div>\n

Global<\/h4>\n<\/div>
<\/div>\n[\/spb_text_block] [spb_parallax parallax_type=”video” bg_image=”12265″ bg_type=”cover” bg_video_mp4=”http:\/\/masdima.pt\/home\/wp-content\/uploads\/2013\/10\/iStock_000014546065Big-Web.mp4″ parallax_video_height=”content-height” parallax_video_overlay=”none” parallax_image_height=”content-height” parallax_image_movement=”fixed” parallax_image_speed=”0.5″ padding_horizontal=”15″ alt_background=”none” el_class=”bt0 bb0 mt0 mb0 no-shadow add-text-shadow” width=”1\/1″ el_position=”first last”]\n

The multi-agent model driven solution<\/span><\/p>\n

We use the Multi-Agent System (MAS) paradigm to represent the roles that exist in the AOC<\/span>
\ncombined with advanced distributed artificial intelligence techniques.<\/span><\/h3>\n

 <\/p>\n[\/spb_parallax] [blank_spacer height=”75px” width=”1\/1″ el_position=”first last”] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” el_class=”mt0 pt0″ width=”1\/3″ el_position=”first”]\n

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Software Agents<\/h3>
A software agent represents each part of the problem\u00a0including its preference and goals: aircraft, crew and passenger. Another software agent represents the global view of the airline company.<\/div><\/div><\/div>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” el_class=”mt0 pt0″ width=”1\/3″]\n
<\/i><\/div>

Automated Negotiation and Learning<\/h3>
Through an automated negotiation process, called Generic Q-Negotiation (GQN), \u00a0the best integrated solution is chosen according to the global interest of the airline. <\/div><\/div><\/div>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” el_class=”mt0 pt0″ width=”1\/3″ el_position=”last”]\n
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Intelligent Decision Making<\/h3>
This results in an autonomous, automated and adaptative system that also includes the human agent in the decision process. Human factors are very important.<\/div><\/div><\/div>\n[\/spb_text_block] [blank_spacer height=”30px” width=”1\/1″ el_position=”first last”] [fullwidth_text alt_background=”alt-ten” el_class=”mt0 mb0 bt0 bb0 no-shadow” width=”1\/1″ el_position=”first last”]\n

MASDIMA\u00a0core features and benefits<\/h1>\n[\/fullwidth_text] [blank_spacer height=”30px” width=”1\/1″ el_position=”first last”] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” el_class=”mt0 pt0″ width=”1\/3″ el_position=”first”]\n
<\/i>

Operational Plan Monitoring<\/h3>

\nIn a 3D visual display the operational plan is monitored in real-time allowing to track flights.<\/p>\n

<\/div><\/div><\/div>\n

 <\/p>\n

<\/i>

Integrated Problem Solving<\/h3>

\nThe 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.
\n<\/div><\/div><\/div>\n

 <\/p>\n

<\/i>

Apply Solution to Operational Plan<\/h3>

\nAfter human approval, the operational plan is updated accordingly including passenger rebooking.
\n<\/div><\/div><\/div>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” el_class=”mt0 pt0″ width=”1\/3″]\n
<\/i>

Event Detection<\/h3>

\nEvents like: aircraft malfunction, weather and ATC restrictions, crew problems, passenger and baggage delay, among others are detected in real-time.
\n<\/div><\/div><\/div>\n

 <\/p>\n

<\/i>

Human in The Loop<\/h3>

\nHuman factors are important. All candidate solutions are presented to the human for feedback and\/or approval.
\n<\/div><\/div><\/div>\n

 <\/p>\n

<\/i>

Simulation<\/h3>

\nMASDIMA 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.
\n<\/div><\/div><\/div>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” el_class=”mt0 pt0″ width=”1\/3″ el_position=”last”]\n
<\/i>

Disruption Impact Assessment<\/h3>

\nThe impact of a disruptive event is assessed in the operational plan of the aircraft, considering all affected crew members and passengers (including missed connections).
\n<\/div><\/div><\/div>\n

 <\/p>\n

<\/i>

Passenger Interaction<\/h3>

\nA 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.
\n<\/div><\/div><\/div>\n

 <\/p>\n

<\/i>

Improve Future Plans<\/h3>

\nMASDIMA can execute an not yet released operational plan, simulating future events and allowing to improve the plan using the simulation results.
\n<\/div><\/div><\/div>\n[\/spb_text_block] [blank_spacer height=”75px” width=”1\/1″ el_position=”first last”] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/1″ el_position=”first last”]\n

Goal Achievement of Our\u00a0Approach<\/span><\/p>\n

Our approach allows to achieve a balanced integrated solution.
\nThis means that each part improves each own goals and at the same time improving the global objective.<\/h3>\n

 <\/p>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/1″ el_position=”first last”]\n

\n
95%<\/span><\/div>\n

<\/div>\n

Aircraft Part<\/h4>\n<\/div>\n
\n
90%<\/span><\/div>\n

<\/div>\n

Crew Part<\/h4>\n<\/div>\n
\n
95%<\/span><\/div>\n

<\/div>\n

Passenger Part<\/h4>\n<\/div>\n
\n
93%<\/span><\/div>\n

<\/div>\n

Global<\/h4>\n<\/div>
<\/div>\n[\/spb_text_block] [blank_spacer height=”75px” width=”1\/1″ el_position=”first last”] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/1″ el_position=”first last”]\n

Recent proof-of-concepts performed with real data show that MASDIMA has the possibility of reducing the cost with IROPS between 10% to 48%, reduce up to 86% the flight delays minutes and increase the passenger satisfaction up to 58% (on average)<\/span><\/p>\n

<\/h3>\n[\/spb_text_block] [blank_spacer height=”75px” width=”1\/1″ el_position=”first last”] [spb_parallax parallax_type=”image” bg_image=”12264″ bg_type=”cover” parallax_video_height=”content-height” parallax_video_overlay=”none” parallax_image_height=”content-height” parallax_image_movement=”fixed” parallax_image_speed=”0.5″ padding_horizontal=”15″ alt_background=”none” el_class=”bt0 bb0 mt0 mb0 no-shadow add-text-shadow” width=”1\/1″ el_position=”first last”]\n

Suitable for all means of transport<\/span><\/p>\n

If your business is getting passengers or cargo from point A to point B, our solution is transport mean-independent.<\/span>
\nEither by air, land or sea, MASDIMA can help you overcome disruptions in the most intelligent cost-effective way.<\/span><\/h3>\n[\/spb_parallax] [blank_spacer height=”75px” width=”1\/1″ el_position=”first last”] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/4″ el_position=”first”]\n

<\/i>\n

Aviation<\/h3>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/4″]\n

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Rail<\/h3>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/4″]\n

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Public Transport<\/h3>\n[\/spb_text_block] [spb_text_block pb_margin_bottom=”no” pb_border_bottom=”no” width=”1\/4″ el_position=”last”]\n

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Logistics<\/h3>\n[\/spb_text_block] [blank_spacer height=”75px” width=”1\/1″ el_position=”first last”] [blank_spacer height=”75px” width=”1\/1″ el_position=”first last”] [spb_text_block title=”Meet our team” pb_margin_bottom=”no” pb_border_bottom=”no” el_class=”mt0 pt0″ width=”1\/4″ el_position=”first”]\n

We believe in a\u00a0multidisciplinary team who has\u00a0been 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.<\/p>\n<\/i>FIND OUT MORE ABOUT US<\/span><\/a>\n

 <\/p>\n[\/spb_text_block] [team item_columns=”3″ item_count=”3″ category=”All” pagination=”no” el_class=”mb0 pb0 mt0 pt0″ width=”3\/4″ el_position=”last”] [blank_spacer height=”13px” width=”1\/1″ el_position=”first last”] [divider type=”thin” text=”Go to top” full_width=”yes” width=”1\/1″ el_position=”first last”] [blank_spacer height=”53px” width=”1\/1″ el_position=”first last”] [spb_text_block pb_margin_bottom=”yes” pb_border_bottom=”no” width=”3\/4″ el_position=”first”]\n\n

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