Routing optimization in goods distribution network by an intelligent transportation system
Subject Areas : تحقیق در عملیاتHasan Daneshvar 1 , Sadegh Niroomand 2 , Omid Boyerhasani 3 , Abdollah Hadi-Vencheh 4
1 - Department of Industrial Engineering, Production Planning and Management, Najafabad Branch, Islamic Azad University, Najafabad, Iran
2 - Department of Industrial Engineering, Firozabad Higher Education Center, Shiraz University of Technology, Shiraz, Iran
3 - Department of Industrial Engineering, Production Planning and Management, Najafabad Branch, Islamic Azad University, Najafabad, Iran
4 - Department of Mathematics, Faculty of Basic Sciences, Khorasgan Branch, Islamic Azad University, Isfahan, Iran
Keywords: Intelligent transportation system, clustering algorithm, Goods distribution network routing, Meta-Heuristic Algorithm,
Abstract :
Considering that finding a suitable route in daylight hours and busy city with traffic restrictions is a big problem that not only causes non-optimal performance in distribution networks, in this regard, after modeling the problem in the form of vehicle routing development VRP) and considering the traffic and time window constraints and its NP-hard, using genetic metaheuristic algorithms (GA) and particle swarm optimization (PSO) to solve the problem and the optimal route and the number of vehicles required to send The product is specified. Customers' locations are first created using the clustering algorithm, location-based clusters, and sub-clusters according to the delivery time window, then a user interface receives the origin and destination provided by the user as input, this interface with Google Map Connection Receives directions between source and destination. Proposed routes are created using the proposed algorithms and using VANET network routing protocols, route events such as traffic are announced and, if necessary, the vehicle travels from the alternative route. The proposed method has better results than the optimal answers in terms of minimizing distance and number of vehicles.
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