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A Research On The Basis Of Large Aircraft Customization Of The Vendor Selection Method And Its Model

Posted on:2017-07-05Degree:MasterType:Thesis
Country:ChinaCandidate:Q ChenFull Text:PDF
GTID:2349330503995623Subject:Transportation planning and management
Abstract/Summary:PDF Full Text Request
As the source of airbus supply chain, the selection of suppliers would direct impact the airbus safety, technology, total cost, delivery time of the whole machine, customer satisfaction, etc. The correctness of selection is the determinant factor for the aircraft manufacturing enterprise core competency. More importantly, to better meet customer demand, the aircraft manufacturing enterprises' vendor selection are affected.Against this background, the existing problems in airbus supplier selection and traditional supplier selection, firstly analyzed the characteristic of airbus development, classified suppliers' and determined tier one suppliers as the main research object. And then concluded the supplier selection characteristics and process flow for the development of airbus; The market rules was first introduced into selection guidelines and evaluation indicators applied for airbus suppliers and described using the Taguchi function; According to the research of the application scope and advantages and disadvantages of several supplier selection methods, this paper proposed multi-objective programming with preference for selection. Aiming at single product multiple sourcing and multiple products multiple sourcing airbus purchases with price discount of the supply chain, 0-1 multi-objective nonlinear integer programming models were set up respectively. In the end, genetic algorithm was applied to solve the model and compared with the AHP and weighted TOPSIS method. The result of the typical examples verified the usefulness of the algorithm and the superiority of the improved model.
Keywords/Search Tags:Large aircraft Manufacturing, Multiple supplier selection, Multi-objective Programming, Civil Airplane Customization, Genetic Algorithm
PDF Full Text Request
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