The project aims to optimize vehicle routes in a Vehicle Routing System using JavaScript, emphasizing user interaction and visualization. It starts by defining the problem scope, understanding requirements, selecting algorithms, and setting up the groundwork. The implementation involves distinct components:
Route Representation: Generates routes with depots, measuring fitness based on covered distance. Genetic Algorithm (GA) Operations: Manages route populations, selects superior routes, and applies crossover and mutation for solutions. Location Representation: Handles delivery locations, visually represented on canvas and DOM for user interaction. User Interface: Provides an interactive platform for modifying locations, depot settings, and observing optimized routes. The Chromosome class generates route solutions, assessing their effectiveness based on covered distance. The GA proceeds by creating diverse initial solutions, evaluating and ranking them, employing selection mechanisms like roulette wheel selection for reproduction, crossover for new solutions, and mutation for diversity. The smooth integration between Chromosome and GA classes ensures efficient evolution and exploration of optimal solutions. The User Interface development focuses on web basics for user-friendly engagement, while Location Representation manages data and visualization of individual locations. Integrating backend technologies aligns front-end functionalities, ensuring seamless interaction and efficient data handling. Overall, this project seeks to solve the Vehicle Routing Problem through a well-integrated approach involving algorithmic optimization and user-centric interface design.