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ROBUST PASSENGER ORIENTED AIRLINE SCHEDULING CADARSO, Luis; MARÍN, Ángel

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ROBUST PASSENGER ORIENTED AIRLINE SCHEDULING CADARSO, Luis; MARÍN, Ángel ROBUST PASSENGER ORIENTED AIRLINE SCHEDULING CADARSO, Luis; MARÍN, Ángel ROBUST PASSENGER ORIENTED AIRLINE SCHEDULING Luis Cadarso, Universidad Politécnica de Madrid, [email protected] Ángel Marín, Universidad Politécnica de Madrid, [email protected] ABSTRACT In scheduled air transportation, airline profitability is influenced by the airline's ability to construct flight schedules. To produce operational schedules, airlines engage in a complex decision-making process, referred to as airline schedule planning. Because it is impossible to simultaneously solve the entire airline schedule planning problem, the decisions required have historically been separated and optimized in a sequential manner. We propose a multi-objective integrated robust approach for the schedule design phase, considering the passenger behaviour, deciding jointly flight frequencies and timetable. The objectives are passengers' satisfaction and operator costs. We try to fix the timetable ensuring that enough time is available to perform passengers' connections, making the system robust avoiding misconnected passengers. Some test networks are solved in order to demonstrate the achieved robustness and choose an appropriate objective. Keywords: robustness, airline schedule design, multi-objective. INTRODUCTION Commercial aviation operations are supported by what is probably the most complex transportation system and possibly the most complex man-made system in the world (Barnhart and Cohn, 2004). Airports represent the nodes on which the system is built. Aircraft represent the very valuable assets that provide the basic transportation service. Passengers demand transportation between origins and destinations, and request specific travel times. Crews operate the aircraft and provide service to passengers. These entities are coordinated through a flight schedule, comprised of flight legs between airports. In order to produce operational schedules, airlines engage in a complex decision-making process, referred to as airline schedule planning. Most of the time the schedule planning starts from an existing schedule. Then, changes are introduced to the existing schedule to reflect changing demands and environment; this is referred to as schedule development. 1 ROBUST PASSENGER ORIENTED AIRLINE SCHEDULING CADARSO, Luis; MARÍN, Ángel However, we will suppose that a coldstart is needed, that is, we must create the schedule planning from scratch. There are three major components in the schedule development step. The first step, the schedule design, is arguably the most complicated step of all. This step is the one we will treat in this work. The purpose of the second step of schedule development, fleet assignment, is to assign available aircraft types to flight legs such that seating capacity on an assigned aircraft matches closely with flight demand and such that costs are minimized. In base to these flows the network is decomposed into sub networks, each one associated only with a particular fleet type. Given these sub networks, the assignment of individual aircraft to flight legs is done in the aircraft maintenance routing step, the third step. Crew scheduling involves the process of identifying sequences of flight legs and assigning both the cockpit and cabin crews to these sequences. The final goal in airline scheduling is to integrate all phases into a single one. Integrated models would optimize schedules, capacities, pricing and seat inventory. However integrating the planning phases is a big challenge: dynamics and competitive behaviours, organizational coordination... Traditionally the schedule design has been decomposed into two sequential steps. The first, the frequency planning, in which planners determine the appropriate service frequency in a market; and the second one, the timetable development, in which planners place the proposed services throughout the day, subject to network consideration and other constraints. Airline schedule design, including how to determine a network's type, flight frequencies and timetable for each flight leg, is a prerequisite for any airline's operational planning such as fleet assignment, routing and crew assignment. Network design is heavily important since the chosen network type, flight frequency and timetable directly influence the operating effectiveness of the airline and the quality of service provided to passengers. Designing an airline network is an extremely complex task due to the huge number of variables affecting the design, i.e. passenger demand, ground facilities and capacity, the competence, etc. These issues are not always easily modelled and usually result in huge models. The most important issue is probably the demand forecasting. Thus, accurately forecasting the future passenger demand on each market is of priority concern in the planning and design of an airline network. However, accumulating a large number of data with good statistical distribution to develop conventional statistical forecasting models is a challenging task. Besides, the uncertainty in other input data also complicates the design of the airline network. For example, a situation frequently arises in which we cannot know the operational costs for possible new routes in the schedule that have not been performed before. Airlines try to generate the lowest possible operating costs and achieve a higher load factor, while passengers concern about flight frequencies, nonstop flights, and in case of stops minimum stop time. 2 ROBUST PASSENGER ORIENTED AIRLINE SCHEDULING CADARSO, Luis; MARÍN, Ángel In case of intermediate stops in itineraries, passengers must perform a flight connection. In order to accomplish this connection an undetermined time is needed by passengers. Airlines usually design itineraries trying to make big enough connection time. However, this issue makes passengers to be dissatisfied. In order to avoid this situation, a new robustness criterion is introduced. Every intermediate stop will always have a minimum connection time; however, this time will not be enough in some situations. In order to avoid misconnected passengers, a penalty based on statistical data is proposed. In this way, expected misconnected passengers will be penalized, but also accounting for passengers’ dissatisfaction. State of Art Generally, the approach is to cast these problems as network design models. In the past, there have been efforts to improve the profitability of the schedule. Simpson (1966) presents a computerized schedule construction system that begins by generating demand using a gravity model, then solves the frequency planning problem and, finally, constructs a flight schedule and solves vehicle optimization problem upon that schedule. Chan (1972) provides a framework for designing airline flight schedules covering route generation and route selection. The previous presented work was performed before deregulation of the passenger air transportation industry in 1978. Soumis, Ferland and Rousseau (1980) consider the problem of selecting passengers that will fly on their desired itinerary with the objective of minimizing spill costs. No recaptures are considered. Flight schedules are optimized by adding and dropping flights. When flights are added or dropped, their heuristic recalculates demands only in markets with significant amounts of traffic. Then, the passenger selection problem is resolved. Their method can be viewed as an enumeration of all possible combinations of flight additions and deletions. Marín and Salmeron (1996) apply the frequency planning to rail freight transportation. The formulation of the rail freight transportation design model is based on the modelling of the physical network, the services and the demand. They study the problem with the help of non- convex optimization models which they solved using heuristic methods to obtain the solution for realistic networks. Marín, Barbas and Gallo (1999) propose a model where the timetable was developed from the frequency planning. The objective is in general to minimize the total passenger delay cost. Armacost et al. (2002) describe a new approach for solving the express shipment service network design problem. Under a restricted version of the problem, they transform conventional formulations to a new formulation using what they term composite variables. The formulation relies on two key ideas: first, they capture aircraft routes with a single variable, and second, package flows are implicitly built into the new variables, the composite variables. Lately, researchers have focused on determining incremental changes to flight schedules, producing a new schedule by applying a limited number of changes to the existing schedule. 3 ROBUST PASSENGER ORIENTED AIRLINE SCHEDULING CADARSO, Luis; MARÍN, Ángel Lohatepanont and Barnhart (2004), in their incremental optimization approach select flight legs to include in the flight schedule and simultaneously optimize aircraft assignments to these flight legs. Garcia (2004) extends the previous model and proposes a combination between it and a decision time window model. Lan, Clarke and Barnhart (2006) consider passengers who miss their flight legs due to insufficient connection time. They develop a new approach to minimize passenger misconnections by retiming the departure times of flight legs within a small time window. They present computational results using data from a major U.S. airline and showing that misconnected passengers can be reduced without significantly increasing operational costs. Kim and Barnhart (2007) consider
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