Optimization of selecting codeshare flights in aviation
Sammanfattning: Airlines are constantly on a look out for partnerships that could facilitate an increase in revenue without having to invest as much. Codesharing is one such solution, where a marketing carrier sells the tickets on another carrier’s flight as its own with its flight number. The codeshares are highly advantageous as they provide new itineraries for the passengers to choose from and increase the traffic for the airline without having to operate the flights. The selection of codeshare flights can be time consuming, for the planners, in the absence of tools that help in the decision making. It not only requires a thorough network analysis but the legal and technical constraints to the codeshares have to be considered as well. This thesis aims to perform a research about the different kinds of codeshares and codeshare agreements along with the major decision factors that affect the choice of an airline to choose a codeshare partner. The primary purpose of this thesis is to provide a prototype tool that can be developed further and be integrated into the Industrial optimizers’ MP2 software (Multiple purpose/ multiple processing optimization software), a tool used by the transport industry for network planning. The prototype support-tool is designed particularly for the marketing carrier with the devised algorithms which provides a possible method to perform the analysis considering the different options and constraints in regards to the selection of behind and beyond codeshare flights and itineraries. The tool processes the available data after which the feasible itineraries are built with respect to the technical, legal and planner specific constraints. To predict the number of passengers who would choose the newly created itineraries, two different models which are based on utility values have been evaluated. The historic passenger choices with the most important factors that affect them are used to create the utility values. The expected passengers and the possible revenues that can be gained from the itineraries then create the base for the final optimization model that suggests the best codeshare flight, along with the expected number of passengers on each itinerary that it is a part of.It should be noted that the revenue management and revenue spilt ups have not been considered in detail for the tool, the most common and simple methods have been considered to perform the analysis, although the different kinds of revenue split ups have been a part of the research, so as to implement them in the MP2 software when required.
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