کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10348474 | 699487 | 2005 | 22 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Active guided evolution strategies for large-scale vehicle routing problems with time windows
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
We present a new and effective metaheuristic algorithm, active guided evolution strategies, for the vehicle routing problem with time windows. The algorithm combines the strengths of the well-known guided local search and evolution strategies metaheuristics into an iterative two-stage procedure. More precisely, guided local search is used to regulate a composite local search in the first stage and the neighborhood of the evolution strategies algorithm in the second stage. The vehicle routing problem with time windows is a classical problem in operations research, where the objective is to design least cost routes for a fleet of identical capacitated vehicles to service geographically scattered customers within pre-specified time windows. The presented algorithm is specifically designed for large-scale problems. The computational experiments were carried out on an extended set of 302 benchmark problems. The results demonstrate that the suggested method is highly competitive, providing the best-known solutions to 86% of all test instances within reasonable computing times. The power of the algorithm is confirmed by the results obtained on 23 capacitated vehicle routing problems from the literature.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Operations Research - Volume 32, Issue 6, June 2005, Pages 1593-1614
Journal: Computers & Operations Research - Volume 32, Issue 6, June 2005, Pages 1593-1614
نویسندگان
David Mester, Olli Bräysy,