Forecasting of Transportation cost for Logistics data

Aim of the paper is to analyze the issues and challenges faced by the transportation sector under supply chain. Optimization of the distance and reduction of transportation cost is one of the major challenge for the Retail Industries. The experiment aims at analyzing the minimum distance required for transporting the products from one or more warehouse to number of costumers. Experiment is based on the execution of Travelling salesman problem (TSP) using branch and bound and dynamic algorithms. Cost and time complexity are analyzed for varied number of costumers. This paper also predicts the Transportation cost using Regression Algorithm, which helps Retail sector to predict the cost incurred for logistics. Also Hypothesis for multiple regression coefficients are conducted to determine statistical evidence is sufficient for given parameters.