1 A Hybrid Approach to Vehicle Routing using Neural Networks and Genetic Algorithms
نویسندگان
چکیده
A competitive neural network model and a genetic algorithm are used to improve the initialization and construction phase of a parallel insertion heuristic for the vehicle routing problem with time windows. The neural network identifies seed customers that are suitably distributed over the entire geographic area during the initialization phase, and the genetic algorithm finds good parameter settings in the route construction phase that follows. Computational results from a standard set of problems are also reported. K e y w o r d s . Vehicle Routing, Time Windows, Neural Networks, Genetic Algorithms. Section
منابع مشابه
A Hierarchy Topology Design Using a Hybrid Evolutionary Algorithm in Wireless Sensor Networks
Wireless sensor network a powerful network contains many wireless sensors with limited power resource, data processing, and transmission abilities. Wireless sensor capabilities including computational capacity, radio power, and memory capabilities are much limited. Moreover, to design a hierarchy topology, in addition to energy optimization, find an optimum clusters number and best location of ...
متن کاملA New Hybrid Routing Algorithm based on Genetic Algorithm and Simulated Annealing for Vehicular Ad hoc Networks
In recent years, Vehicular Ad-hoc Networks (VANET) as an emerging technology have tried to reduce road damage and car accidents through intelligent traffic controlling. In these networks, the rapid movement of vehicles, topology dynamics, and the limitations of network resources engender critical challenges in the routing process. Therefore, providing a stable and reliable routing algorithm is ...
متن کاملA Multi-Objective Imperialist Competitive Algorithm for Vehicle Routing Problem in Cross-docking Networks with Time Windows
This study addresses the pickup and delivery problem for cross-docking strategy, in which shipments are allowed to be transferred from suppliers to retailers directly as well as through cross-docks. Usual models that investigate vehicle routing in cross-docking networks force all vehicles to stop at the cross-dock even if a shipment is about to a full truckload or the vehicle collects and deliv...
متن کاملA Hybrid Metaheuristic Algorithm for the Vehicle Routing Problem with Delivery Time Cost
This paper addresses the Vehicle Routing Problem with Delivery Time Cost. This problem aims to find a set of routes of minimal total costs including the travelling cost and delivery time cost, 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. In this research, a hybrid metaheuristic approa...
متن کاملPrediction of Gain in LD-CELP Using Hybrid Genetic/PSO-Neural Models
In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...
متن کامل