Abstract:

Objective Warp beams in a textile mill occupy large storage space and are difficult to manage due to their dimensional diversity and heavy-duty characteristics, representing an urgent problem to be solved in the intelligent manufacturing process in textile enterprises. An automated warehouse together with a suitable scheduling algorithm need to be designed and implemented.
Method A next generation of algorithm solution was developed through genetic, cross, mutation and other operations, which aimed to eliminate the solution with lower fitness function value and maintain the solution with higher fitness function value. By improving the mutual variation function, the exploration ability of the algorithm was improved, and the optimal storage matrix was designed to ensure that the optimal task result would not be eliminated by the algorithm, and the convergence condition of the algorithm is improved. For the task under different working conditions, the most reasonable iteration times are designed to ensure that the optimal solution is obtained while reducing the operation time, so that the algorithm time is shorter and the optimization ability is stronger.
Results On the basis of the traditional stereoscopic warehouse, the structure of the designed side-flow dual station rack significantly improves the storage density of materials. The warehouse layout is reorganized, and the rack area is reasonably divided, including large pallet head, small pallet head and independent parts of yarn shaft, so as to ensure the efficient classified storage of various pallet shaft types. This structural improvement not only optimizes space utilization, but also facilitates fast access and management of stored materials. The application of dynamic adjustment genetic algorithm greatly improves the operation efficiency of the crane. In the actual task test, the algorithm was applied to four different scenarios, including 2 inbound and 4 outbound tasks, 8 inbound tasks and 6 outbound tasks, 10 inbound tasks and 12 outbound tasks, 15 inbound tasks and 10 outbound tasks. In the four experiments, the optimization scheduling time is reduced by about 21% at most, and compared with the simulated annealing algorithm scheduling strategy under four sets of different working conditions, the first three experiments show that the optimized genetic algorithm has stronger exploration ability and faster iteration speed, with the increasing complexity of the working conditions, the initial working time is 490 s, the optimization result of the optimized genetic algorithm is 383 s, and the result of the simulated annealing algorithm is 420 s, and the optimization genetic algorithm makes the algorithm have a stronger ability to jump out of the suboptimal solution, which can effectively improve the efficiency of the warehouse outbound operation. The algorithm simplifies the material handling process by carefully adjusting crane movements and sequencing task sequences, and reducing the frequency of cross-region scheduling.
Conclusion In order to solve the problem that the circular warp warehouse of large textile enterprises cannot meet the effective scheduling requirements of multiple goods, a side-flow shelf type stereoscopic warehouse was proposed. At the same time, the optimization problem of in/out route was solved, and the optimization strategy of dynamic adjustment genetic algorithm was applied. The problem of low operation efficiency and low utilization of storage space of the stacker crane was solved by optimizing the warehouse management and the inbound/outbound operation path. The optimized algorithm can avoid local optimization in genetic algorithm, ensure search efficiency and optimal iteration times under different working conditions. The experimental results show that the improved algorithm has a higher exploration ability, and can effectively improve the efficiency of operations. The optimization scheme provides theoretical and technology support for improving production efficiency and intelligent warehouse management.

Key words: heavy-duty flange and warp beam, shelf type stereoscopic warehouse, universal tray, genetic algorithm, scheduling optimization, intelligent textile factory, warehouse management