07 اردیبهشت 1403
غلامرضا احمدي

غلامرضا احمدی

مرتبه علمی: مربی
نشانی: دانشکده مهندسی جم - گروه مهندسی کامپیوتر (جم )
تحصیلات: کارشناسی ارشد / فناوری اطلاعات
تلفن: 07737646160
دانشکده: دانشکده مهندسی جم

مشخصات پژوهش

عنوان An Improved Hybrid Cuckoo Search Algorithm for Vehicle Routing Problem with Time Windows
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
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مجله Journal of Quality Engineering and Production Optimization
شناسه DOI
پژوهشگران امین رضایی پناه (نفر اول) ، غلامرضا احمدی (نفر دوم) ، مهدی حاجیانی (نفر سوم) ، محمدرضا درزی (نفر چهارم)

چکیده

Transportation in economic systems such as services, production and distribution enjoys a special and important position and provides a significant portion of the country's gross domestic product. Improvements in transportation system mean improvements in the traveling routes and the elimination of unnecessary distances in any system. The Vehicle Routing Problem (VRP) is one of the practical concepts in the field of investigation and many attempts have been made by researchers in this area. Due to the importance of transportation issues in the real world and the status of these issues in the types of existing systems. In this paper, we investigate the Vehicle Routing Problem with Time Window (VRPTW) and provide a solution for it. The problem of routing vehicles with a time window is an extension of the problem of routing vehicles with limited capacity (CVRP) in which servicing must be done in a specific time window. The purpose of this problem is to optimize the route for each vehicle so as to minimize the total cost of the route and the number of vehicles used, and ultimately maximize customer satisfaction. In the paper, a hybrid method based on cuckoo search and greedy algorithm is proposed to solve the problem of VRPTW. For the cost function, different criteria have been used that are within the framework of the VRPTW problem within hard and soft constraints. In order to evaluate the proposed method, the dataset is used in different sizes. The proposed method is significantly higher compared to similar methods.