IEEE Computational Intelligence Magazine - May 2022 - 93
after rearrangement because a rearranged
timetable with less change compared
to the original timetable is preferred.
Hong et al. [121] considered the
uncertainty of flight time, which
induced an uncertain arrival time. The
proposed approach not only addresses
the landing sequencing problem but also
schedules the flight routes of airplanes to
enter the airport. PSO is used to generate
a landing sequence, while flight
route scheduling is modeled as a mixedinteger
linear programming problem
and solved by the CPLEX Optimizer
(software developed by IBM).
B. Intelligent Airline Management
Airline management refers to the management
of various affairs in airline
operations. The objective of airline management
is to maintain the orderly
operation of airlines and to maximize
profit. Thus, airline management is considered
from the business perspective.
EC algorithms are widely used to solve
airline management problems, including
flight planning, airplane assigning, airplane
maintaining, crew scheduling, and
shuttle arranging.
1) Flight Planning
Flight planning aims to generate a flight
schedule that maximizes the profit of
the airline and includes the following
two steps. The first step is to select a set
of flights from many candidate flights to
operate. This selection is restricted by
the number of available airline resources
(e.g., number of airplanes and employees).
Kölker and Lütjens [122] used GA
to solve this problem. After selecting a
set of flights, the second step is to specify
the timetable of these flights to obtain a
complete flight schedule. Abdelghany
et al. [123] used GA to solve this problem
and considered three optimization
objectives: maximizing ticket revenues
and the number of flight rotations, and
minimizing the idle time of airline
resources. The number of flight rotations
refers to the number of flights that an
airplane and a group of crew members
can conduct consecutively.
However, during the operation of
the flight schedule, certain disruptions
may occur, such as poor weather, air
traffic control restrictions, and airplane
breakdown. In this case, the flight schedule
must be rearranged to maintain
flight operations and to minimize delays
[124]. Another possible solution for disruptions
is inserting buffer time when
arranging the original timetable. In
addition to the necessary ground turnaround
time between two consecutive
flights (e.g., boarding/offboarding time,
airplane maintenance time), some buffer
time is added. Thus, if a previous flight is
delayed, the subsequent flight can still be
on time. Ahmed et al. [125] used PSO to
determine the buffer time between two
consecutive flights to avoid flight delays.
Although the insertion of buffer time
may lose some potential profit, buffer
time can avoid rearranging the flight
schedule and enhance the on-time performance
of an airline, which is one of
the issues that passengers are concerned
about the most.
2) Airplane Assigning
After determining the flight schedule,
airlines should assign airplanes to fly all
planned flights. Zhang et al. [126] used
ACO to minimize the time required to
finish all flights. Chou et al. [127] proposed
a multiobjective GA with the two
objectives of ensuring sufficient ground
turnaround time between two consecutive
flights and minimizing the number
of no-profit flights. If the destination of
the previous flight is different from the
departure of the subsequent flight, the
airplane needs to conduct a flight to the
departure of the subsequent flight with
no passenger. Such a flight refers to a
no-profit flight.
In addition, different flights have different
numbers of potential passengers.
The flights between two large cities typically
have many passengers. Different
types of airplanes have different capacities
(e.g., the number of seats). Thus,
assigning a suitable airplane for each
flight can yield more profit. Anzoom
and Hasin [128] used an ACO-based
algorithm to optimize the profit of an
airline, where the profit was calculated
by subtracting the flight operating cost
from the ticket revenue. Yazdi et al. [129]
made a more comprehensive calculation
of the revenue, which considered ticket
revenues and the revenue obtained from
ticket cancelations and overbooking. A
binary DE is used, and the solution is
encoded by a matrix representing the
map between airplanes and flights.
In recent years, scientists find that a
large number of carbon emissions will
cause global climate warming. Therefore,
the assignment of airplanes should also
consider carbon emissions [130]. The
European Union (EU) has launched the
EU Emissions Trading System (EUETS)
that restricts the carbon emissions
of flights whose departure or destination
is in EU countries. If the carbon emissions
exceed the limit, the airline should
pay a fine based on the exceeded emissions.
Ko et al. [131] dealt with the regulation
of EU-ETS by assigning airplanes
with low carbon emissions for flights in
the EU, and GA is used to optimize the
profit of the airline.
3) Airplane Maintaining
Safety is the primary issue in flight.
Insufficient maintenance can cause an
airplane to crash, yielding many casualties.
The crash of China Airlines Flight
611 in 2002 killed all 225 people in the
airplane, and the investigation showed
that it was caused by metal fatigue in the
tail skin [132]. To ensure the safety of
flights, airplanes require regular maintenance.
Because airplanes continuously
fly from one destination to the next to
earn profits, an airline must determine
when and where to perform maintenance
of airplanes in accordance with
the regulation made by the International
Civil Aviation Organization. For
example, routine maintenance must be
performed if an airplane meets the
maximum cumulative flight time.
Flights may be delayed for various reasons,
which will cause the maintenance
plan to fail to proceed as scheduled.
Eltoukhy et al. [133] proposed an ACObased
algorithm to address the coordination
between flight operation and
maintenance operation. A bilevel model
is proposed, which uses the upper and
lower levels to minimize the delay of
flights and the employment cost for
MAY 2022 | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE 93
IEEE Computational Intelligence Magazine - May 2022
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