Optimum Research On Warehousing System Based On Genetic Algorithm

Selection of job order in warehousing system has a great influence on theefficiency of warehousing management. For improving warehousing work capacitybetter, decreasing losses brought by bad arrangement of job order and improvingeconomic benefits of warehouses in enterprises, the paper uses genetic algorithmused for simulating organic evolution process to make optimization research onsuch problems as moving path of the stacking machine, goods loading and haulway.Genetic algorithm is a general problem-solving method based on the idea of organicevolution, and its essence is a parallel global searching method used for solvingproblems. It can automatically acquire and accumulate knowledge about searchingspace in searching process, and it can control self-adaptively searching processto acquire optimal solution. The paper uses the compiled general program forgenetic algorithm to make numerical experiment research, and the result indicatesthat genetic algorithm can solve optimization problems of all kinds ofcomplicated functions. Controlling parameters in genetic algorithm, such aspopulation size, coding length of chromosomes, crossover probability, mutationprobability and evolutionary generation, has an important influence onperformance of genetic algorithm. By analyzing operating procedure of thestacking machine in detail, and factors influencing operational efficiency ofthe stacking machine, the paper designs optimization scheme for location of thewarehouse, puts forward the optimization model for moving path of the stackingmachine, and uses genetic algorithm to optimize moving path of the stackingmachine with ten tasks and acquires the global optimal solution. As for the boxingproblem confronted frequently in transporting field of warehousing, the paperestablishes mathematical model for loading problems of scattered goods. And theresearch indicates genetic algorithm can well solve loading problems of scatteredgoods under all kinds of constraint conditions. In addition, by using geneticalgorithm, the paper makes optimization research on transporting route of vehiclein warehousing center. The paper uses genetic algorithm as optimization methodfor optimization-seeking problems in warehousing system, and practice indicatesthe algorithm is very effective to be a heuristic algorithm of high performancewhich can be used for solving combinatorial optimization problems.