Speaker recognition using discrete wavelet transform and artificial neural networks

الملخص EN

Pickup and delivery problems constitute an important class of vehicle routing problems in which objects have to be collected and distributed.

This paper discusses a heuristic approach called Repetitive Nearest Neighbour Algorithm to solve Travelling Salesman Problem, to determine the tour the vehicle should follow so that the total distance travelled is minimized.

The algorithm was tested in planning the best route which connects a set number of shops; the shops were distributed within an area of 20km by 20km, also the algorithm used to locate the best seed when computing the optimum tour.

The overall minimum cost computed for cases of different shop numbers, between 10 and 500 shops.

The coordinates for each shop on an X,Y map was generated and recorded, then a distance matrix was calculated which shows the cost of traveling between all shops in km.

The computation time for the algorithm was recorded for each case.

The aim of this paper is to apply a Traveling Salesman Problem (TSP) algorithm to solve real world problems by helping traffic managers of freight transport companies to reduce operational costs via shorter routes and optimized distribution maps..

In order to do so effectively, TSP implementation is to be optimized to reduce computation time.

In this paper, a nearest neighbour greedy algorithm based approach for solving the TSP effectively is presented.