Meta-Heuristics Algorithms of Intelligent Parking System on a Rush Hour Centre in Space Transport and Propulsion
Keywords:
Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Genetic Particle Swarm Optimization (GA-PSO), Matric, Laboratory (MATLAB) Program, Centre Space Transport and Propulsion (CSTP).Abstract
Abstract
The search for parking space is a time consuming process which not only affects the economic activities efficiency, but also the social interactions and cost. The need for efficient parking management systems especially during rush hour cannot be emphasized enough for such cities. Therefore, this study seeks to provide a solution to the issues by hybridizing two algorithms: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) during rush hour in space transport and propulsion at a particular city Epe in Nigeria. This was measured by some metrics parameter such as Time-taken, Cost and User-satisfaction to solve the problem of premature convergence. The three algorithms: (GA-PSO, PSO and GA) using a Matric Laboratory (MATLAB) program in an intelligent parking system tried to allocate the route for the user vehicle in an optimal manner. GA-PSO solved the parking allocation problems by obtaining minima values in terms of the cost and time taken with high user satisfaction. The experimental results demonstrated an accurate and robust car parking space allocation algorithm. In return, a GA-PSO based car parking space allocation algorithm produced a reliable car parking allocation system.
