برنامه ریزی تصادفی دو مرحله ای فاصله فازی
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برنامه ریزی تصادفی دو مرحله ای فاصله فازی

عنوان فارسی مقاله: برنامه ریزی تصادفی دو مرحله ای فاصله فازی شهودی بهبود یافته برای مدیریت برنامه ریزی منابع ادغام کننده تاوان بازگشت از کمبود و مازاد منابع
عنوان انگلیسی مقاله: An improved intuitionistic fuzzy interval two-stage stochastic programming for resources planning management integrating recourse penalty from resources scarcity and surplus
مجله/کنفرانس: مجله تولید پاک – Journal of Cleaner Production
رشته های تحصیلی مرتبط: مهندسی محیط زیست
گرایش های تحصیلی مرتبط: آب و فاضلاب
کلمات کلیدی فارسی: برنامه ریزی دو مرحله ای فاصله ای، برآورد مرز تولید، قیمت حدودی، مجموعه های فازی شهودی، برنامه ریزی منابع آب
کلمات کلیدی انگلیسی: Interval two-stage programming، Production frontier estimation، Shadow price، Intuitionistic fuzzy sets، Water resources planning
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.jclepro.2019.06.183
دانشگاه: Center for Agricultural Water Research in China, China Agricultural University, Beijing, 100083, China
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 7.096 در سال 2018
شاخص H_index: 150 در سال 2019
شاخص SJR: 1.620 در سال 2018
شناسه ISSN: 0959-6526
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 15
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E12837
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


1. Introduction


2. Methodology


3. Case study


4. Result analysis and discussion


5. Conclusions


Acknowledgments


References

نمونه متن انگلیسی مقاله

Abstract


Two-stage programming (TSP) is popular in resources planning management, especially for limited and precious resources. Remarkable study has been done to improve the model performance. However, one of the biggest obstacle is lack of objectivity when it comes to penalty quantification derived from recourse behavior. Besides, much attention has been paid in the resources deficiency penalty but little in resources residual, which may lead to wasting. In order to clarify the physical meaning of mathematical equation for recourse penalty from both resources scarcity and surplus, the production frontier was estimated and the technical efficiency and shadow prices of resources were introduced into TSP to characterize the resources deficiency and residual penalty, respectively. Then, an intuitionist fuzzy interval two-stage stochastic programming (IFITSP) was generated integrating the uncertainty of fuzzy membership and traditional TSP. An integrated solving approach was proposed coupling several previous uncertain programming methods and an improved robust interval TSP method. A case study was conducted in an arid area of northwest China to schedule agricultural cultivation scale based on limited water resources. The inefficiencies were [0.26, 0.49], [0.14, 0.37] and [0, 0.03] for GZ, LZ, and GT. The shadow prices of GZ, LZ, and GT in 2015 were 12.94, 2.61, 2.67 Yuan/m3 respectively, indicating the sever water crisis of GZ. The relatively unbiased and abundant decision could be generated by the developed IFITSP to help decision makers with various preferences make tradeoff between benefits and basic crop production requirement as well as balance resources deficiency and surplus. The results also show that the developed model could unveil the uncertainty influence of model inputs on decision strategies and trigger managers to deeply analyze subjective effect and associated risk. By comparison, the proposed methodology can not only clarify the physical meaning of penalty but deal with more complex uncertainty than previous methods. Therefore, the established model can provide reliable and scientific support for resources planning with recourse.


Introduction


Resources scarcity is threatening human sustainable development around the world. Climate change, population growth, environmental contamination and industrial expansion have worsened the resources crisis which urges managers to develop high-efficient resources management approaches (Singh, 2012). In response to mitigating the resources crisis, the reasonable resources planning is among the most popular resources management and has been widely discussed worldwide. Remarkable contributions have been done surrounding the optimal resources planning and one of the achievements is twostage programming (TSP), which is capable of modifying the predetermined targets (called first-stage decision) based on the overall influence of uncertain events and generating corresponding decision (called second-stage decision) after the uncertain events happen. Resources planning optimization research on TSP covers all walks of life, ranging from agriculture (Fu et al., 2018; Zhang et al., ۲۰۱۷), hydrology (Ding et al., 2017; Hu et al., 2016; Yu et al., 2016), environment (Han et al., 2012; Han et al., 2013; Han and LEE, 2011), energy (Yun et al., 2017), and transportation (Barbarosoglu and Arda, 2004) to medicine (Dillon et al., 2017), manufacture (Alfieri et al., 2012), and networks (Wu and Kucukyavuz, 2018). A highlighted part in TSP is penalty quantification caused by uncertain events, which is usually expressed as benefits loss from resources deficiency according to previous studies. However, the previous achievements share two problems.

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