کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1757560 1523014 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A multi-objective fuzzy linear programming model for optimization of natural gas supply chain through a greenhouse gas reduction approach
ترجمه فارسی عنوان
یک مدل برنامه ریزی خطی چند منظوره برای بهینه سازی زنجیره تامین گاز از طریق یک روش کاهش گازهای گلخانه ای
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علوم زمین و سیاره ای (عمومی)
چکیده انگلیسی


• This study evaluates and optimizes natural gas supply chain.
• A multi-objective multi-period fuzzy linear programming model is proposed.
• Economic and environmental objectives are considered in the model.
• A combination of possibilistic programming approach is used for solving the model.

Natural gas is one of the most important sources of energy for many of the industrial and residential users in the world. It has a complex and huge supply chain which is in need of heavy investments in all the stages of exploration, extraction, production, transportation, storage and distribution. The aim of this study is evaluation and optimization of natural gas supply chain using a multi-objective multi-period fuzzy linear programming model considering economic and environmental objectives. In the proposed model, to deal with uncertainty, the parameters of problem including demand, capacity and cost are considered as fuzzy parameters. To solve the problem, a combination of possibilistic programming approach based on previous approach is used to verify and validate the model. A small-sized problem was solved using GAMS 23.2 software and sensitivity analysis is conducted on its parameters. To the best of our knowledge, this is the first study that presents a multi-objective fuzzy linear programming model for optimization of natural gas supply chain through a greenhouse gas reduction approach.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Natural Gas Science and Engineering - Volume 26, September 2015, Pages 702–710
نویسندگان
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