Automatic STORAGE & Retrieval System Order Picking Job Scheduling Optimization Research

The first profit source of enterprises is trying to reduce the cost of labor and materials,the second is expanding market sales, and the third is reducing logistics cost. Nowadays the manufacturing system is developing rapidly, so much so that its high efficiency increasingly become a mismatch with the low efficiency of logistics system. In the manufacturing process of enterprises, Automatic Storage & Retrieval System plays a critical role in the logistics process of materials and finished products. It is a complex system with random jobs. Unreasonable production scheduling of the system will greatly reduce its operation efficiency, thus affecting the operational efficiency of enterprise. When the Automatic Storage & Retrieval System is faced with large quantities of fast jobs with high strength, if the jobs were only operated in accordance with their arrival sequance without consideration to their internal conflicts and the competition within shared resources, etc., the effective running time of the system and the operational efficiency of the stacker cannot reach the optimal standard, which will largely reduce the system’s operating efficiency. Therefore, the optimization of job scheduling is particularly important. In terms of this problem, this paper mainly completed the following work:①In terms of the complexity of job scheduling of the Automatic Storage & Retrieval Systems, this paper carries on a deep analysis on the composition and the working process of the system, as the task of screening jobs increases, the scheduling combination presents exponential growth,elaborates the optimization problem of job scheduling from the physical perspective,.and proposes the conception of the consumed time of the variable part of job scheduling②In terms of the optimization problem of job scheduling of the Automatic Storage & Retrieval Systems, this paper establishes a comprehensive model through hybird Petri net and a order picking job scheduling model of Petri net, and puts forward the mathematical expression of the consumed time of the variable part of job scheduling optimization and the consumed fixed time, studying the job scheduling optimization problem from the mathematical perspective.③In terms of the problem that the job scheduling of the Automatic Storage & Retrieval Systems cannot reach the optimal standard when faced with the exponential growth of the scheduling combination, this paper, based on job scheduling model of Petri net, designs an intelligence algorithm based on Petri net combined with improved genetic algorithm to optimize the job scheduling, and apply the algorithm to a job scheduling example,and comparing the optimized results with standard genetic algorithm’s optimized results, the designed algorithm is verified that the algorithm we designed is better for automated warehouse job scheduling optimization by the comparison.④In terms of the job scheduling simulation model, We design three experiments that stacker machine adopts different scheduling policies while simulating. We verify the effectiveness of the algorithm that we designed based on Petri net combined with improved genetic algorithm through the analysis of statistical data for job scheduling optimization process, and compared the advantage of standard genetic algorithm’s optimization.