کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1133667 1489076 2015 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The vehicle routing problem with multiple prioritized time windows: A case study
ترجمه فارسی عنوان
مشکل رانندگی خودرو با چندین پنجره اولویت بندی شده: یک مطالعه موردی
کلمات کلیدی
بهینه سازی چند هدفه، مشکل مسیریابی خودرو با چندین پنجره زمان بندی اولویت بندی شده، الگوریتم ژنتیک کوانتومی چند هدفه هماهنگی تعاونی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
چکیده انگلیسی


• We introduce a multi-objective vehicle routing problem with multiple prioritized time windows (VRPMPTW).
• A mathematical model and a cooperative coevolutionary quantum-genetic algorithm are proposed to solve the VRPMPTW.
• A new local search are designed and used in CCMQGA to reach an appropriate Pareto front.
• The results show that the proposed algorithm can reach a better Pareto set compared with NSGAII and MQEA results.

This paper addresses Multi-objective Vehicle Routing Problem with Multiple Prioritized Time Windows (VRPMPTW) in which the distributer proposes a set of all non-overlapping time windows with equal or different lengths and the customers prioritize these delivery time windows. VRPMPTW aims to find a set of routes of minimal total traveling cost and maximal customer satisfaction (with regard to the prioritized time windows), starting and ending at the depot, in such a way that each customer is visited by one vehicle given the capacity of the vehicle to satisfy a specific demand. This problem is inspired from a real life application. The contribution of this paper lies in its addressing the VRPMPTW from a problem definition, modeling and methodological point of view. We developed a mathematical model for this problem. This model can simply be used for a wide range of applications where the customers have multiple flexible time windows and violation of time windows may drop the satisfaction levels of customers and lead to profit loss in the long term. A Cooperative Coevolutionary Multi-objective Quantum-Genetic Algorithm (CCMQGA) is also proposed to solve this problem. A new local search is designed and used in CCMQGA to reach an appropriate pareto front. Finally, the proposed approach is employed in a real case study and the results of the proposed CCMQGA are compared with the current solution obtained from managerial experience, the results of NSGA-II and the multi-objective quantum-inspired evolutionary algorithm.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 90, December 2015, Pages 402–413
نویسندگان
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