شماره مدرك :
3402
شماره راهنما :
3221
پديد آورنده :
شهبازي، احسان
عنوان :

موازنه زمان - هزينه در شبكه هاي داراي زمان هاي احتمالي (PERT) با استفاده از الگوريتم ژنتيك

مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
مهندسي صنايع
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده صنايع و سيستم ها
سال دفاع :
1385
صفحه شمار :
نه، 81، [II] ص.: جدول، نمودار
يادداشت :
ص. ع. به فارسي و انگليسي
استاد راهنما :
علي حاج شيرمحمدي
استاد مشاور :
مهدي بيجاري
توصيفگر ها :
نظريه احتمالات , برنامه ريزي خطي، پويا , شبكه هاي پرت
استاد داور :
رضا حجازي
تاريخ ورود اطلاعات :
1395/12/07
كتابنامه :
كتابنامه
رشته تحصيلي :
صنايع و سيستم ها
دانشكده :
مهندسي صنايع و سيستم ها
كد ايرانداك :
ID3221
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتال
چكيده انگليسي :
AbstractThe purpose of this research is to show a new approach to time cost trade off problem innetworks with probabilistic times and finding the answer using Genetic Algorithm GA In general we have three basic model for time cost trade off in projects Our objective in thisresearch is for situation condtaining a tim constraint on project completion So if we want toperform the activities in an ordinary time it is impossible to finish the project at that time Therefore with using resources with better quality and quantity which needs spending directcost we can decrease the time of activities in which delays would cause delay in the wholeproject time critical path activities In order to know how much time we need to decreasefrom those activities we have to describe time cost trade off problem in project control In thisresearch we use two basic assumption in PERT networks First in order to calculate meantime of activities we use three time estimation system related to PERT networks Second wecan use different resources with different time and cost for each activity for executing eachactivity In order to solve this problem with those assumptions we present a non linearprogramming model can be solved by GA The results show that Lingo Software has somemore acceptable results in comparison to GA but executing time of GA was considerablyshorter than Lingo Software especially with the situations where the problem scales weremagnified Comparing the results of solving the non linear programming model with the helpof genetic algorithm and Lingo software showed the strength of proposed algorithm
استاد راهنما :
علي حاج شيرمحمدي
استاد مشاور :
مهدي بيجاري
استاد داور :
رضا حجازي
لينک به اين مدرک :

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