Research On Scheduling Optimization Of Automated Warehouse Based On PSO

Automated storage and retrieval system(AS/RS) is the outstanding result of the development of such modern logistics technology, storage technology and automation technology, which is the integration of storage, transportation and distribution. Automated storage and retrieval system is being applied more and more widely and composed of many subsystems. To improve the operation of automated warehouse efficiency, automated warehouse unloading scheduling optimization is important to study theoretical and engineering significance.Based on application and development requirements of modern logistics, this paper puts emphasis on the research of slotting optimization and algorithm stability in AS/RS used intelligence theory particle swarm optimization(PSO).The main contents and innovations are as follows:This paper proposed and implemented hybrid particle swarm optimization for solving scheduling and slotting optimization problems. The multi-object function is built by the stability of storage and picking time. During the solution process, PSO is used to initialize to improve the search performance of the algorithm and optimize results, this method improve the optimization efficiency and shorten the search time. During the iterative process, using the simulated annealing algorithm to avoid premature convergence and getting in local optimum of conventional PSO, because this method has the probabilistic jumping ability. Examples show that the algorithm compared with the genetic algorithm, with a shorter time, faster convergence and fewer iterations.This paper analyzed the inertia weight and acceleration factors on the convergence performance of PSO, proposed four kinds of inertia weight and two kinds of acceleration factors adjustment strategy. Using three kinds of test functions for adjustment strategy test. Examples show that the algorithm with adjustment strategy compared with the standard PSO, the algorithm convergence performance was improved.This paper analyzed the algorithm stability, based on the test results fromthe different shelves form factors and the different scale problems. The convergence performance of the algorithm is affected by shelves shape factor is not big and not sensitive. With the increase of problem size, algorithm has the stable convergence performance.To demonstrate and verify the model, using Java programming language and database support environment to develop AS/RS scheduling management system. On the basis of the analysis about the basic needs of the system,implemented the optimization algorithm of matlab program real time calls and completed the AS/RS automation control in the process of scheduling.