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Optimal time and minimum cost Algorithm in networks

خوارزمية الزمن الأمثل و الكلفة الأقل في الشبكات

1959   1   91   0 ( 0 )
 Publication date 2014
and research's language is العربية
 Created by Shamra Editor




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Operational research science aims to find the optimal solution to many problems in various life domains. One of the most famous is the network analysis. Problem. In this paper we introduce an effective algorithm with linear time O ( n + k ) within it all network activities are executed within determined period and with a minimum cost.

References used
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Chase, Richard., Operations Management, .MC Graw – Hill, New Delhi 2006
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Federal Transit Administration, Project and Construction Management Guideline, USA.,2003
Geoff Whitty and Emma Wisby " Real Decision Making? School Councils in Action" © Institute of Education, University of London 2007
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في المشكلة التي نعالجها, تحتاج شركة اتصالات إلى بناء مجموعة من الأبراج الخلوية لتوفير خدمة الاتصالات الخليوية للسكان في منطقة جغرافية. تم تحديد عدد من المواقع المحتملة لبناء الأبراج. يعتم اختيار هذه المواقع على عدة عوامل ، بما في ذلك مدى اتساق البرج مع البيئة المحيطة وارتفاع التضاريس, تتمتع الأبراج بمدى تغطية ثابت ، وبسبب قيود الميزانية ، لا يمكن بناء سوى عدد محدود منها . بالنظر إلى هذه القيود ، ترغب الشركة في توفير تغطية لأكبر قدر ممكن من السكان, والهدف هو اختيار في أي من المواقع المحتملة يجب أن تقوم الشركة ببناء الأبراج. إن المشكلة التي شرحناها يمكن نمذجتها لتصبح أحد أمثلة مشكلة 0/1 knapsack الشهيرة لذلك شرحنا في الحلقة مفهوم مشكلة 0/1 Knapsack والطرق المستخدمة في الحل, وتوسعنا في الشرح عن خوارزمية Branch and Bound كونها تعتبر أفضلها.
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Recently, a class of tracking techniques called "tracking by detection" has been shown to give promising results at real-time speeds. These methods train a discriminative classifier in an online manner to separate the object from the background. This classifier bootstraps itself by using the current tracker state to extract positive and negative examples from the current frame. Slight inaccuracies in the tracker can therefore lead to incorrectly labeled training examples, which degrade the classifier and can cause drift. In this paper, we show that usingSimple Online and Realtime Tracking (SORT) which is a pragmatic approach to multiple object tracking with a focus on simple, effective algorithms
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