پديد آورنده :
غفاري ديزجي، ميثم
عنوان :
ارائه يك مدل مكان يابي هاب در حمل و نقل هوايي با استفاده از شبكه هاي صف و با تقاضاي فازي
مقطع تحصيلي :
كارشناسي ارشد
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده صنايع و سيستم ها
صفحه شمار :
يازده،91ص.: مصور،جدول،نمودار﴿رنگي﴾
يادداشت :
ص.ع.به فارسي و انگليسي
استاد راهنما :
علي شاهنده
توصيفگر ها :
برنامه ريزي غير خطي عدد صحيح , شبكه صف جكسون , الگوريتم ژنتيك و الگوريتم بهينه سازي تجمع ذرات , برنامه ريزي محدوديت - شانس , شبيه سازي فازي , الگوريتم ژنتيك تركيبي
تاريخ نمايه سازي :
28/1/92
استاد داور :
نادر شتاب بوشهري، محمدسعيد صباغ
دانشكده :
مهندسي صنايع و سيستم ها
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
92 A hub location model in air transportation using queuing networks with fuzzy demand Meisam Ghafari Dizaji m ghafaridizaji@in iut ac ir Date of Submission 2013 01 9 Department of Industrial Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Ali Shahandeh ali nook@cc iut ac ir Abstract Hub location problem is of new issues and branch of location problems which is presented in recent decades Hub location problem is flow transportation from the origin to the destination In the network hub instead of a direct connection between both the origin and destination flow are transported through the hubs In this study a network hub and spoke are designed for air transport where the sum of the travel times and waiting times at hubs is considered simultaneously To calculate the waiting time at hubs each hubs is considered as open Jackson network including four components of M M c queuing systems consisting landing unloading areas loading areas and take off Flow passing through each hub are separated to input and output flows from them Optimum arrival rate to each hub and then the average waiting time at each hub is done with the location of hubs and allocation non hub simultaneously The proposed model is a mixed integer nonlinear programming Due to the complexity of the model the exact solution will be found a long time so metaheuristic methods including genetic and particle swarm optimization algorithms is used to solve the proposed model Also the performance of the metaheuristic algorithms is compared In this study also is used fuzzy approach to proposed model The demand between nodes is considered as fuzzy variables This problem is modeled with chance constrained programming For solving chance constrained programming is used fuzzy simulation based genetic algorithm Keywords Hub location Mixed integer nonlinear programming Queuing Jackson network Genetic and Particle swarm optimization algorithms Chance constrained programming Fuzzy simulation based genetic algorithm
استاد راهنما :
علي شاهنده
استاد داور :
نادر شتاب بوشهري، محمدسعيد صباغ
