Approximate Optimization Model on Routing Sequence of Cargo Truck Operations through Manila Truck Routes using Genetic Algorithm

Abstract

Genetic Algorithms are algorithms used for search, optimization, and machine learning. It is designed to mimic the natural process of selection where the fittest individuals survive. As such, it is applied fields of mathematics and science. One of which that it can be applied to is routing, which can also be a solution to the worsening traffic congestion most cities throughout the world continuously experience. Although its economy is rigorously growing with its expanding cargo transport and logistics industry and that land transport is its dominant mode of moving goods, the Philippines exhibits poor quality management in its traffic. One of the several solutions proposed to address this problem is by restricting large trucks because these are perceived as slow moving and occupants of large road space. The objective of this study is to propose an approximate optimization model by applying genetic algorithm that would give an optimum routing sequence for freight trucks assuming these trucks start from Manila's port area, to final destinations of northern (Northern Luzon Expressway or NLEX), southern (Southern Luzon Expressway or SLEX), and eastern alternate routes (Marcos Highway), and back to the port area. The algorithm was able to produce 480 best generations, and has provided the shortest and more reasonable total distance of 68.73 km.