Storage Assignment And Task Schedule Of Active Dense Automated Storage And Retrieval System

Active dense automated storage and retrieval system combines the technique of dense storage and automatic warehouse so that it can not only store and retrieve automatically, but also save the cost of space. In order to increase the utilization of space, the SKUs whose quantities are small can be applied with mixed storage.This paper analyses the outbound process of active dense automated storage and retrieval system with mixed storage and finds that there is a condition that the SKU needs to be delivered may be blocked by others. So it is necessary to move the obstructive SKU to another location on the shelf and then obtain and deliver the objective SKU. This process can be called’remove obstacle’. There is no doubt that remove obstacle will decrease system’s outbound efficiency. Then two ideas to optimize the outbound efficiency are proposed:decreasing the possibility of remove obstacle by location assignment optimization and reducing the operation time of stacking truck by outbound task schedule optimization.As to the optimization of location assignment of active dense automated storage and retrieval system, this paper transfers the goal from decreasing the possibility of remove obstacle to clustering the SKUs whose correlation are high firstly. Secondly, a mathematical model is set up and then solved by two clustering algorithms. This paper applies hierarchical clustering algorithm and then proposes a dynamic clustering algorithm based on an evaluation function and using the result of hierarchical clustering algorithm as initial solution. Finally, this paper uses Matalab to simulate based on the data of a cigarette distribution center and concludes that the dynamic clustering algorithm based on evaluation function is better.As to the optimization of task schedule of active dense automated storage and retrieval system, this paper analyzes the outbound path and time of stack struck, and then establishes a mathematic model whose target is minimizing the outbound time firstly. Secondly, this paper proposes the principles of task schedule and remove obstacle. Thirdly, this paper solves the mathematical model by two algorithms which include a heuristic algorithm based on the principles mentioned before and a genetic algorithm. Finally, this paper uses Matalab to simulate based on the data of a cigarette distribution center. It concludes that both two algorithms can reduce the outbound time and the heuristic algorithm can obtain a better result.