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A Study of Balancing and Sequencing Problems of Mixed-mode Assembly Lines
Author: HuangYuKai
Tutor: TangQiuHua
School: Wuhan University of Science and Technology
Course: Mechanical Manufacturing and Automation
Keywords: mixed-model assembly Balancing Production sequencing Genetic algorithm
CLC: F273
Type: Master's thesis
Year: 2011
Downloads: 85
Quote: 1
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Abstract
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Two key problems in mixed assembly line are balancing and sequence. Key research ofbalancing problem is to balance load between each workstation. Sequence problem mainlydiscusses the production order of products. With the quality of the products and customerdemand more and more personalized, the complexity of balancing and sequence escalates.Balancing and sequence problem have been proven to NP-hard problem.In this paper, We mainly analysis difficulty and significance of the study on mixed-modelassembly line balancing and sequencing according to the characteristics of the hybrid assemblyline, discuss the evaluation indicators of the problem of balancing and the key elements whichclosely related with the sequencing problem. Then, establish the mathematical modelsrespectively according to different optimization objectives of the balancing and sequencingproblem.Based on the mathematical model, the improved genetic algorithm is designed aimed at thebalancing and sequencing respectively, then designs a two-level scheduling genetic algorithm byconnecting with the balancing and sequencing problems, finally, realizes the model solutionbased on the algorithm.Finally, improve the results of the algorithm are excellent by a large number of examples.Simultaneously, Highlights the advantages and disadvantages of the algorithm by comparingwith results calculated by the method which transform the mixed-model assembly line balancingproblem into a single assembly balancing problem, on the other hand, it improves themathematical mode and the improved genetic algorithm can optimize the hybrid assembly lineand have practical significance.
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CLC: > Economic > Economic planning and management > Enterprise economy > Production management
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