کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6854650 | 1437591 | 2019 | 36 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Evolutionary learning algorithm for reliable facility location under disruption
ترجمه فارسی عنوان
الگوریتم یادگیری تکاملی برای مکان قابل اطمینان در محل اختلال
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کلمات کلیدی
سلام، قابلیت اطمینان، بهینه سازی ترکیبی، یادگیری تکاملی، اهریمنی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Facility location represents an important supply chain problem aiming at minimizing facility establishment and transportation cost to meet customer demands. Many facility location problem (FLP) instances can be modelled as p-median problems (PMP) and uncapacitated facility location (UFL) problems. While, most solution approaches assume totally reliable deployed facilities, facilities often experience disruptions and their failure often leads to a notably higher cost. Therefore, determination of facility locations and fortification of a subset of them within a limited budget are crucial to supply chain organizations to provide cost effective services in presence of probable disruptions. We propose an evolutionary learning technique to near-optimally solve two research problems: Reliable p-Median Problem and Reliable Uncapacitated Facility Location Problem considering heterogeneous facility failure probabilities, one layer of backup and limited facility fortification budget. The technique is illustrated using a case study and its performance is evaluated via benchmark results. We also provide an analysis on the effects on facility location by prioritizing customer demands and adopting geographic distance calculation. The approach allows fast generation of cost-effective and complete solution using reasonable computing power. Moreover, the underlying technique is customizable offering a trade-off between solution quality and computation time.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 115, January 2019, Pages 223-244
Journal: Expert Systems with Applications - Volume 115, January 2019, Pages 223-244
نویسندگان
Badr Afify, Sujoy Ray, Andrei Soeanu, Anjali Awasthi, Mourad Debbabi, Mohamad Allouche,