پديد آورنده :
مجلسي نسب، ناهيد
عنوان :
طراحي مدل مكان يابي هاب با هدف بيشينه سازي پوشش مورد انتظار تقاضا
مقطع تحصيلي :
كارشناسي ارشد
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده صنايع و سيستم ها
صفحه شمار :
ده،93ص.: مصور،جدول،نمودار
يادداشت :
ص.ع.به فارسي و انگليسي
استاد راهنما :
علي شاهنده
توصيفگر ها :
مسئله بيشينه پوشش هاب , سرويس دهنده , سيستم صف , الگوريتم ژنتيك , الگوريتم جستجوي ممنوعه
تاريخ نمايه سازي :
17/6/92
استاد داور :
قاسم مصلحي، نادر شتاب بوشهري
دانشكده :
مهندسي صنايع و سيستم ها
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Designing a Hub Location Model to Maximize Expected Coverage of Demand Nahid Majlesi Nasab n majlesinasab@in iut ac ir Date of Submission 2013 01 14 Department of Industrial and Systems Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Ali Shahandeh Ali nook@cc iut ac ir Abstract Nowadays postal networks air transportation systems and tourism companies use Hub Maximal Covering Model in order to benefit its economies of scale and optimal flow covering between origins and destinations But some hub nodes get congested specially in peak hours and this lead to improper covering and consequently an inefficient hub and spoke network Common Hub Maximal Covering Models could not prevent this undesirable event These models suppose that hub nodes always are available and there are an infinite number of servers for each hub In order to handle this problem this study considers hub nodes as an M M C queuing system individually Then three Maximum Expected Hub Covering Location Models are presented in which busy probability of hub nodes is considered In the first model busy probabilities of the servers are considered equal and the number of servers in different hubs is the same In order to strengthen the model the second model is presented which supposes busy probabilities and the number of servers in different hubs is not the same and given This model uses the current number of servers in the hubs and might not be optimal to service the network Finally the third model is presented which determines the optimal number of servers considering various busy probabilities for servers in different hubs Since the proposed models are NP hard two Metaheuristic algorithms based on Genetic Algorithm and Tabu Search are developed Computational results on the US domestic air transportation network in 2011 peak hour show that in addition to covering radius busy or free probability of servers has an important effect on locating hubs and allocating non hubs to hubs Also computational results on the US domestic air transportation network show the proposed algorithms are efficient and can give near optimal solutions in a short time Keywords Location Hub Maximal Covering Server Queuing system Genetic Algorithm Tabu search Algorithm PDF created with pdfFactory trial version www pdffactory com
استاد راهنما :
علي شاهنده
استاد داور :
قاسم مصلحي، نادر شتاب بوشهري
