Computation of vehicle allocation, scheduling and number of commuters in selected Nigerian routes

Abstract

The research is aimed at developing a transport management algorithm that will be used to determine the number of commuters and vehicular allocation with high numerical accuracy. Many research works have proposed either using machine learning algorithms for clustering, classification, determination of frequent item-set in datasets (databases) or traditional algorithms to effectively design transportation systems. In this research a non-machine learning algorithm that does not require any training time, which will require less computation power and increase process execution time is developed. The scheduling algorithm is designed taking note of two most important variables: the number of commuters is the independent variable and the number of buses assigned or schedule to a designated route is the dependent variable. Some decision assumptions are made which include all vehicle used in the research have same carrying capacity for all the routes. The algorithm numerically computes the number of commuters, the number of assigned vehicles and the number of scheduled vehicles for each route. So, the research will assist in making useful deductions such; number of resources required to effectively service a route without bottle-necks and more accurately the size of input per route and approximate output for the corresponding routes. The results show the total number of vehicles assigned, scheduled and number of commuters on a text file (document).