American Airlines Managment Essay Research Paper American — страница 3

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allocation of these factors to production. One of the first inputs into logistical programming is the supply schedule, which is the main determinant of the amount of products or services offered by a firm. For the airline industry, supply schedules manifest themselves in the form of the magnitude of flights offered to the public. A demand forecast is the main force behind the supply schedule, but other normative microeconomic factors play an important role in its composition. One of these factors, optimal scale of plant, exerts a direct relationship against the supply schedule and, for American Airlines, consists of the optimal terminal/gate layout at its busiest hub cities. The goal of proper terminal design is to optimize the number and size of the complexes which converge on a

hub terminal throughout the day. A complex consists of a group of inbound flights which land within minutes of each other and take-off within minutes of each other. This is the very heart of a hub and spoke system which allows a large number of flights due to the number of possible connections in the hub. Inbound passengers from many cities will all arrive at approximately the same time, disembark, and make connections to many outbound flights which leave within minutes of each other. This occurs many times throughout the day and the system requirement for solving this problem and optimizing the operation is available in the form of CADD design stations. CAD/CAM design workstations may be used to solve terminal optimization problems and allow engineers to simulate the capability

of the terminal to handle certain scenarios. This is, in fact, exactly what American Airlines did when it was searching for the optimum design for its $80 million expansion of its main hub in Dallas/Fort Worth in 1983. This simulation model was used by senior management to aid them in their decision on the best design to handle the desired flow of traffic in the narrow operational time constraints necessary for the hub to work. In addition to optimizing the terminal layout, the system was useful in optimizing other related areas. The system/model was used to determine dynamic gate assignments in order to minimize baggage handling costs and passenger delays. Another byproduct of the model was a useful algorithm designed to automatically program and update signs for directing

passengers around the terminal. The functional facility was even used to determine the best layout for short-term parking in the face of expected increases in passenger traffic. Though optimal scale of plant through optimal terminal design is an important aspect of American Airlines? supply schedule determination, the most important part of the supply schedule lies in determining the number of flights to and from certain destinations. For American Airlines and most of the airline industry, flight scheduling is not a simple matter. Flight scheduling is one of the most important tasks performed by tactical airline managers because it is central to where and how the factors of production are allocated. The technical system requirements are myriad, and they must meet the daunting

problem of properly scheduling thousands of flights per day between hundreds of domestic and international destinations using a fleet of over 500 aircraft. One main requirement is for a system capable of analyzing past flight offerings in search of patterns of overbookings and empty flights in order to adjust schedules to better meet forecasted demand. Technical requirements for an airline scheduling system would include a data base structure to house the body of past and present schedules from which managers could choose when composing a new schedule. The problem is compounded since airline schedules are determined months in advance. In addition to using optimization techniques, the system requires certain expert system facilities such as decision table constructs to aid in

schedule development. Diagnostic remedial aids are used in order to spot bottlenecks in the proposed schedules where patterns of frequent overbookings are occurring. In addition, remedial systems capable of offering solutions by reshuffling proposed schedules provides valuable information to flight scheduling managers. Historical data is fed into the scheduling model from the database containing past schedules and data concerning past parameters which influenced those schedules. The system takes this data and combines it with the demand forecast in order to develop a preliminary schedule. The process requires diagnostic and remedial systems to optimize the schedule so that the expected demand will be met in the most efficient manner possible. Even with an optimal schedule in