Genetic Algorithm Application in Route Optimization Using Google Maps API

Abstract

Route planning from several locations is a common problem encountered. Google Maps provides a feature to plan routes from multiple location but does not provide a feature to find the optimal route from these locations. Based on the survey, 61.9% of respondents have a low level of confidence when planning the optimal route from several locations. So we need software that can help in planning the route. This research utilizes genetic algorithms to help plan routes from several locations. The genetic algorithm used includes components in the form of chromosomes, fitness values, selection, crossover, and mutations. In addition, Google Maps API used as the data source that provides maps, directions, and distance matrices. The design method used extreme programming. The software is made using HTML, CSS, PHP, and JavaScript programming languages with MySQL DBMS. In addition, Black-box and White-box testing method is used in this research. The results of this study are route optimization software that works by using genetic algorithm components to obtain optimal route from several locations with the advantages of using Google Maps API and selecting location points and starting points that are flexible. This study aims to highlight the benefits, limitations, and future prospects of route optimization. The findings of this research will contribute to assist decision-makers in adopting effective strategies related to route optimization.