Integrated optimization of storage allocations in automated storage and retrieval system of bearings

To optimize storage allocation in Automated Storage and Retrieval System (AS-RS), it is not sufficient to considering stock-in or stock-out operations individually or separately. In this paper, an optimization model of storage allocation in terms of stock-in and stock-out integration is designed to minimize the energy consumption. Considering the practical issue of bearing corrosion affecting its quality significantly, the measure of bearing corrosion is introduced in the model as constraints. With regards to the complication of the proposed model, a Genetic Algorithm is designed. The status of storage location is coding as Chromosome, the single-point sequential Crossover and exchange-based Mutation are designed in terms of matrix rows and columns, respectively. To ensure the feasibility of chromosomes, a heuristic method is applied to initialize population in a step-by-step manner and a repairing mechanism is introduced to satisfy the corrosion constraints. The simulation results show that, the integrated storage allocation model (ISAM) is effective for minimizing the total energy consumption; the bearing corrosion constraints may significantly influence the optimization result; the designed GA is efficient for solving the model.