دانلود مقاله ISI انگلیسی شماره 51591
ترجمه فارسی عنوان مقاله

روش ادغام AHP-TOPSIS برای اولویت دادن به راه حل اتخاذ لجستیک معکوس برای غلبه بر موانع آن در محیط فازی

عنوان انگلیسی
Integration of AHP-TOPSIS method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
51591 2015 17 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Manufacturing Systems, Volume 37, Part 3, October 2015, Pages 599–615

ترجمه کلمات کلیدی
لجستیک معکوس؛ تاپسیس؛ فازی؛ صنعت الکترونیک؛ هندوستان
کلمات کلیدی انگلیسی
Reverse logistics; AHP; TOPSIS; Fuzzy; Electronics industry; India
پیش نمایش مقاله
پیش نمایش مقاله  روش ادغام AHP-TOPSIS برای اولویت دادن به راه حل اتخاذ لجستیک معکوس برای غلبه بر موانع آن در محیط فازی

چکیده انگلیسی

Reverse logistics practices are gaining attention due to industrial ecology, enforced legislation and corporate citizenship but presence of barriers make reverse logistics (RL) implementation difficult and hence reduce the success rate. To increase RL adoption, robust and flexible strategies are required to overcome its barriers. This study focuses on identification and ranking the solutions of reverse logistics adoption in electronics industry to overcome its barriers. It aids firms to ponder on high rank solutions and develop strategies to implement them on priority. This paper proposes a methodology based on fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to identify and rank the solutions of RL adoption to overcome its barriers. Fuzzy AHP is applied to get weights of the barriers as criteria by pairwise comparison and final ranking of the solutions of RL adoption is obtained through fuzzy TOPSIS. The empirical case of Indian electronics industry is shown to illustrate the use of the proposed method. This proposed method offers a more precise, efficient and effective decision support tool for stepwise implementation of the solutions due to consideration of fuzzy environment. Finally sensitivity analysis is performed to illustrate the robustness of the method.