Research On Path Optimization Of Container Type Stereoscopic Warehouse Based On Coarse-grained Parallel Genetic Algorithm

The path optimization problem of automated warehouse stacker is NP-complete problem,which can not get the optimal solution.Scholars use various optimization algorithms and hybrid algorithms to solve the picking problem of stacker,which obtains a certain effect.However,when the size of the problem is large and the complexity of the problem is high,the efficiency of the traditional optimization algorithm is limited.With the rapid development of hardware technology,it is possible to realize parallel computing.How to make full use of parallel algorithms and make full use of hardware has become a real problem.In this paper,a Single Program,Mutiple Data(SPMD)parallel structure is applied to coarse-grained parallel genetic algorithm and the algorithm is improved.The purpose of this paper is to make the algorithm carry out parallel computing on multi-core computer,improve the performance of the algorithm and shorten the time of operation.In order to improve the coarse-grained parallel genetic algorithm to solve practical problems.In this paper,the improvement of traditional coarse-grained parallel genetic algorithm mainly includes :(1)the optimization of mutation strategy and the improvement of population migration strategy by applying different mutation methods to different sub-populations.(2)the improvement of migration strategy.migrating the individuals between the sub-populations by combining the dynamic mobility adjustment with the complete network topology to n.(3)The serial program of the improved algorithm is adapted to parallel program.On this basis,the improved coarse-grained parallel genetic algorithm based on SPMD parallel method is used to solve the problem model of automated warehouse picking path optimization,and the speedup ratio of parallel computing is calculated according to the results.The comparison shows that the improved algorithm can effectively shorten the operation time and improve the efficiency of solving the path optimization problem of automated warehouse.This study has a certain reference to the research of parallel genetic algorithm and also to the study of parallel computing.It is of great practical significance to solve the problem of route optimization of stacking and picking in automated stereoscopic warehouse.