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- W775834025 abstract "This study explores the mathematical programming aspects of the air cargo fleetassignment problem for one international air cargo carrier - Korean Air - undergiven origin-destination (O-D) pairs, departure and arrival times, and frequencies.A pure cargo service is taken as the basis for this study, since such a service is notconstrained by passenger route determinants and the schedule of a combination aircarrier.The objectives of the study include: to identify the pure air cargo networkrepresentation of the combination air carriers; to develop and solve a conventionalbranch-and-bound mathematical programming model for optimising theassignment of aircraft to flight routes given a set of constraints, including aircraftfleet size, schedule balance, and `required through' constraints; to develop andsolve the fleet assignment problem using a novel neural network optimisationmodelling approach; to investigate methods of implementing the neural networkmodel, and to analyse the performance of the model when compared withconventional solution methods; and finally to analyse the utility of the neuralnetwork model and identify how it may be used in the design and development ofair cargo networks for combination air carriers like Korean Air.There are four main parts to the thesis: the first part outlines the schedule designprocess of an airline and some details of the fleet assignment problem arereviewed. The air cargo flight network is represented and the fleet assignmentproblem is formulated as a mixed integer programming problem of costminimisation with various constraints. The complexity of the problem is discussed;the second part outlines the various techniques available to solve optimisationproblems and neural network models are presented and discussed as a promisingalternative solution method. Neural network applications in the transport field arereviewed and the neural network process for optimisation and for solving thegeneral assignment problem are studied and presented; the third part incorporatesthe practical application of both the conventional fleet assignment problem solvingmethod and the proposed neural network method to a combination airline's case -Korean Air. The detailed process of constructing a time line network andformulating a mathematical programming model are described and equivalentneural network models are formulated. The results from the two solutionapproaches are compared and evaluated; and the final part summarises the mainfindings, presents the significant conclusions, the contribution of the research isdiscussed and some recommendations for further research are presented.Overall, the conventional branch-and-bound optimisation model yieldedplausible results which were demonstrably superior to those produced using thenovel neural network optimisation models." @default.
- W775834025 created "2016-06-24" @default.
- W775834025 creator A5038835460 @default.
- W775834025 date "2000-01-01" @default.
- W775834025 modified "2023-09-23" @default.
- W775834025 title "A neural network approach to air cargo fleet assignment" @default.
- W775834025 hasPublicationYear "2000" @default.
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