کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7499015 | 1485864 | 2018 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Green transportation scheduling with pickup time and transport mode selections using a novel multi-objective memetic optimization approach
ترجمه فارسی عنوان
برنامه ریزی حمل و نقل سبز با انتخاب زمان وانت و انتخاب حالت حمل و نقل با استفاده از رویکرد بهینه سازی چند منظوره جدید
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کلمات کلیدی
برنامه ریزی حمل و نقل، حمل و نقل سبز، بهینه سازی چند هدفه، بهینه سازی تکاملی،
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم محیط زیست
علوم زیست محیطی (عمومی)
چکیده انگلیسی
This paper addresses a green transportation scheduling problem with realistic constraints widely existing in make-to-order manufacturing supply chains, such as pickup time and transport mode selections. The mathematical model of this problem is presented, which is formulated as a bi-objective mixed integer nonlinear program. The problem is simplified first by converting this program to a bi-objective integer nonlinear program. A novel evolution-strategy-based memetic Pareto optimization (ESMPO) approach is then developed to handle this new program, in which a multi-objective local search process is proposed to seek promising neighboring individuals and the faster nondominated sorting procedure is introduced into the memetic algorithm to perform multi-objective sorting. The performance of the proposed ESMPO approach is evaluated by numerical experiments based on industrial data and industrial-sized problems. Experimental results demonstrate that the proposed approach can effectively solve the investigated problem by generating much better solutions than 3 other metaheuristic-based Pareto optimization approaches and the industrial method do.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transportation Research Part D: Transport and Environment - Volume 60, May 2018, Pages 137-152
Journal: Transportation Research Part D: Transport and Environment - Volume 60, May 2018, Pages 137-152
نویسندگان
Zhaoxia Guo, Dongqing Zhang, Haitao Liu, Zhenggang He, Leyuan Shi,