IJE TRANSACTIONS C: Aspects Vol. 30, No. 6 (June 2017) 867-875    Article in Press

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N. Foroozesh and R. Tavakkoli-Moghaddam
( Received: January 29, 2017 – Accepted in Revised Form: April 21, 2017 )

Abstract    For assessing and selecting sustainable suppliers, this study considers a triple-bottom-line approach, including profit, people and planet, and regards business operations, environmental effects along with social responsibilities of the suppliers. Diverse metrics are acquainted with measure execution in these three issues. This study builds up a new hybrid intelligent model, namely COA-LS-SVM, for taking performance variations of the sustainable suppliers quantified by the performance index. The presented artificial intelligent (AI) model is introduced in light of a new combination of least squares-support vector machine (LS-SVM) and cuckoo optimization algorithm (COA). The LS-SVM is used in regards to the mapping capacity amongst performance index and its causative input criteria. The COA is presented to advance LS-SVM tuning parameters. In this exploration, an illustrative database comprising of 80 historical cases is gathered to set up the presented intelligence system. In the light of experimental results, the presented COA-LS-SVM can effectively illustrate performance index’s variances since it has accomplished relatively low statistical metrics. Therefore, the proposed hybrid AI framework can be a promising approach to help the supply chain decision-makers in sustainable supply chain management (SSCM).


Keywords    Computational intelligence, Sustainable supplier selection, Least square-support vector machine (LS-SVM), Cuckoo optimization algorithm


چکیده    به منظور ارزیابی و انتخاب تامین­کنندگان پایدار، این تحقیق یک رویکرد سه قسمتی شامل سود، مردم و سیاره و توجه به عملیات کسب و کار، اثرات زیست محیطی همراه با مسئولیت­های اجتماعی از تامین کنندگان را در نظر می گیرد. متریک­های متنوع با اجرای اندازه گیری، ما را از این سه مسئله مطلع می­سازد. این مقاله یک مدل هوشمند ترکیبی جدید، به نام COA-LS-SVM، برای تعیین کمی تغییرات عملکرد تامین­کنندگان پایدار با استفاده از شاخص عملکرد ایجاد می­کند. مدل پیشنهاد شده هوشمند مصنوعی (AI) ترکیب جدیدی از ماشین بردار پشتیبان با حداقل مربعات (LS-SVM) و الگوریتم بهینه­سازی فاخته (COA) معرفی می­کند. LS-SVM برای بیان ظرفیت نگاشت در میان شاخص­های عملکرد و معیارهای ورودی مسبب آن استفاده شده است. COA به منظور پیشبرد میزان­سازی پارامتر­های LS-SVM پیشنهاد شده است. در این جستجو، یک پایگاه داده متشکل از 80 داده تاریخی برای راه اندازی سیستم هوشمند ارائه شده، جمع آوری شده است. در پرتو نتایج تجربی، از آن-جا که متریک­های آماری نسبتا کم انجام می­گیرد، COA-LS-SVM می­تواند به طور موثری شاخص عملکرد واریانس را نشان دهد. بنابراین، چارچوب AI ارائه شده می­تواند یک روش امیدبخش برای کمک به تصمیم گیرندگان زنجیره تامین، در مدیریت زنجیره تامین پایدار باشد.


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