Optimization of Parking Space Allocation for Automated Parking System of Paternoster Type by Genetic Algorithm

The automated parking system (APS) of paternoster type has the advantages of high parking density, flexible layout and operational economic. In this paper, aiming at the parking and pickup problems in APS of paternoster type, the operational arrangements of this new type of parking system are optimized. A dedicated mathematical model is designed to minimize the operational time of APS subject to the space and operational constraints. To solve the model, a special genetic algorithm is designed, where feasible parking space allocation is represented by a chromosome and a repair process is designed to reserve its feasibility under crossover or mutation. Finally, the simulated experiments are conducted to solve a set of numerical problem instances, and the effectiveness of the proposed method is testified by comparing with the traditional greedy method.