کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5480970 1522098 2017 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multi-objective co-operative co-evolutionary algorithm for minimizing carbon footprint and maximizing line efficiency in robotic assembly line systems
ترجمه فارسی عنوان
الگوریتم هماهنگ تکاملی چند منظوره همکاری برای به حداقل رساندن رد پای کربن و بهره وری حداکثر خط در سیستم خط مونتاژ رباتیک
کلمات کلیدی
تعادل خط مونتاژ روباتیک، رد پای کربن، بهینه سازی چند هدفه، محاسبات تکاملی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
Methods for reducing the carbon footprint is receiving increasing attention from industry as they work to create sustainable products. Assembly line systems are widely utilized to assemble different types of products and in recent years, robots have become extensively utilized, replacing manual labor. This paper focuses on minimizing the carbon footprint for robotic assembly line systems, a topic that has received limited attention in academia. This paper is primarily focused on developing a mathematical model to simultaneously minimize the total carbon footprint and maximize the efficiency of robotic assembly line systems. Due to the NP-hard nature of the considered problem, a multi-objective co-operative co-evolutionary (MOCC) algorithm is developed to solve it. Several improvements are applied to enhance the performance of the MOCC for obtaining a strong local search capacity and faster search speed. The performance of the proposed MOCC algorithm is compared with three other high-performing multi-objective methods. Computational and statistical results from the set of benchmark problems show that the proposed model can reduce the carbon footprint effectively. The proposed MOCC outperforms the other three methods by a significant margin as shown by utilizing one graphical and two quantitative Pareto compliant indicators.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Cleaner Production - Volume 156, 10 July 2017, Pages 124-136
نویسندگان
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