Automated Storage And Retrieval System Modeling And Scheduling Optimization Research

With the rapid development of automation technology and logistics technology, intelligent warehouse has been widely applied over the world. Intelligent warehouse is widely used in the following two ways. Firstly, the smart warehouse is applied in modern manufacturing on automatic production lines and provincial electric energy metering equipment verification center undering construction in the past two years, storing final products(electric energy metering equipment)or accessories. Secondly, with rapid development of e-commerce, there appear large Internet companies in recent years, such as Jingdong, Taobao. In order to meet the needs of enterprise development, they have invested a lot in building its own logistics center. Therefore, the efficiency of intelligent storage has become one of the important roles improving logistics efficiency.Autonomous vehicle storage and retrieval system(AVS/RS) as a new intelligent warehouse is first proposed by American professor Malmborg and his colleagues in 2003, which has got great attention of many scholars in Europe afterwards. For AVS/RS is not widely used in applications, it is necessary to establish an appropriate scheduling model and develop reasonable operating rules for simulation and optimization of AVS/RS's operation. This paper focused on the theme of AVS/RS with scheduling optimization of multiple rail guided vehicle (RGV) and multipe lift. The issues of system control, decision-making, scheduling and three-dimensional simulation are modeled and solved. The main contributions of this paper are in the following folds.(1) A decision analysis model of AVS/RS with multi-RGV and multi-lift is proposed. The objective task is considered as a customer, RGV is considered as a secondary resource, elevator is considered as a server. Thereby, a semi-open queuing network (SCQN) is formed. In the network, each arriving customer associates a secondary resource, customers and secondary resources call the required set of server in specific sequence. Firstly, the storage task scenarios and retrieval task scenarios coupled with probability of occurrence are defined.Secondly, the running time of elevator and RGV in all possible positions are calculating. Then, scenario is modeled as a client, which can be aggregated into a DCQN model. Finally, the DCQN model is solved and the performance is evaluated, the best ratio of car and lift is obtained to help making decision in terms of optimizing the system design, improving equipment utilization and saving cost.(2) According to layout of AVS/RS with multi-RGV and multi-lift, optimal mathematical model of the RGV single retrieval/storage operation and compound operations are established.Firstly,rules of RGVs and lifts operating are defined, the RGV single retrieval/storage operation, compound operations and their decomposition process are analyzed. A mathematical model based on the shortest path and the shortest time of AVS/RS with multi-RGV and multi-lift are established. In addition, the time of RGV's horizontal movement and lift's vertical movement are defined. Finally, the complexity of the scheduling problem is analyzed,and the model for AVS/ RS with multi-RGV and multi-lift has achieved promising significance.(3) According to the scheduling optimizal mathematical model of AVS/RS with multi-RGV and multi-lift described in this article, a discrete artificial fish swarm algorithm (DAFSA) is proposed to solve the model.An encoding and decoding method is designed, which contains RGV task allocation and elevator selection information. Individual behavior and optimization process in DAFSA are optimally designed respectively. Dynamic vision range and discrete adaptive step are introduced to accelerate the convergence speed. Communication behavior is increased to enhance the direction of individual optimization.The surviving mechanism of the fittest groups appropriate is introduced to update the population so as to enhance the diversity of the population.Test functions are used to test the stability of DAFSA.The other two algorithms, ABC and QPSO are compared with DAFSA, the results prove the effectiveness and superiority of DAFSA. An improved Dijkstra is introduced to find out the RGV's horizontal path in different stages, which is transformed into the problem of solving K shorest path planning so as to solve the path planning of RGV in horizontal direction.(4) The conflicting control strategy based on the banker's algorithm-iterative time window of AVS/RS with multi-RGV and multi-lift is proposed. Firstly, the work process is divided into two stages. The improved Banker's algorithm is used to pre-judge the type of conflict by two phases. The conflicting policy of processing the possible nodes or arc is used to reduce the computation time. Secondly, iterative time window algorithm is used to eliminate conflicts so as to improve the utilization of RGV, while enhancing the system securit. Through comparative studied, the effectiveness of modified Banker's algorithm based on time window conflicts control strategies is verified. A blocking delay analysis model is established. The number of RGVs, cargo space,the shelves' ratio of depth to width that impaction of system blocked delay is analyzed.(5) A three-dimensional displaying platform of AVS/RS with multi-RGV and multi-lift that based on the 3D-MAX technology is introduced. Firstly, the overall scheme of three-dimensional display platform is described, which included the proposal and implementation of a three-dimensional model. Scheduling model and conflict control strategy presented in the previous chapters are verified by examples in the displaying platform. The impact of shelf layers, the number of RGVs and lifts, the size of the task in the algorithm are analyzed. Experimental results show that the dynamic displaying platform can simulate the actual operation of the system so as to provide great support for the actual operation of the system.