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|Title:||Multi vehicle routing problem||Authors:||Vasumathi Lakshmi Raghavan||Keywords:||DRNTU::Engineering::Electrical and electronic engineering||Issue Date:||2018||Abstract:||We all dream of a perfect start to any day- the sound of music, the work ethic of humans, the moments of joy but instead we rise up to the traffic congestion which makes our start to the day miserable and unforgettable. Inspite of proper traffic light system in the peak hour, we still endure the problem of traffic jams. The research in this area keeps increasing and we are yet to figure out a proper routing method to just come to a conclusion which is actually not possible. This problem is becoming more challenging by the day due to the variation in the traffic network and various other constraints. In order to develop an on-demand route guidance, one needs to track and predict the traffic congestions. This can be developed if we are able to predict how the traffic emerges, figure out the peak hour traffic jams and determine route guidance schemes. The need of hour is to have a proper traffic management system. Through this project “Multi Vehicle Routing Problems” traffic management can be implemented using Vehicle Routing Algorithms [VRP], the generalization of Travelling Salesman Problem, where the aim is to find the optimal set of rules for the fleet vehicles delivering goods or services to various locations in Singapore. This VRP also has some constraints that needs to be addressed. Some of them include the time, distance, capacity, number of locations and so on. This project aims to concentrate on the minimal distance and the number of assigned and the unassigned jobs. It also aims to reduce pollution, transportation cost, fuel problem etc. which indirectly leads to develop a better country. The method followed here involves the “pick-up” and “drop-off” point, that deals with the number of the unassigned jobs in this case, and also the address for delivering to the desired location. In order to deliver to the destined locations the capacity of the vehicle is also taken into consideration. This routing algorithm follows local search metaheuristic and first solution strategy. This project will give a way to decide which method to follow to reduce the traffic congestion although the problem persist in a long run.||URI:||http://hdl.handle.net/10356/73134||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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