Automatic Positioning Method of Optimal Warehouse in Smart Power Grid Supply Chain Based on Improved Genetic Annealing Algorithm
In order to solve the problems of material dispersion,information confusion and low operation efficiency in the ware-house under the supply chain,and with the goal of improving the warehouse management level and ensuring the supply and de-mand time of warehouse transportation,an optimal warehouse automatic positioning method is put forward to improve the smart power grid supply chain.This paper establishes the objective function with the shortest transportation time.This paper improves the genetic annealing algorithm,select the chromosomal coding mode,set the automatic positioning constraints,con-struct the supply and demand model between the power grid material warehouses,the optimal warehouse can be automatically positioned with the optimal supply and demand relationship.The experimental results prove that after applying the proposed method,the change trend of each cost changing with the penalty cost is relatively flat,and the proportion of demand not met in time is positively correlated with the total cost.The positioned warehouse meets the target impact function,and the target function of the optimal warehouse positioning is obtained with 62 iterations.It can alleviate the contradiction in power material scheduling,and improve the transportation efficiency of power grid material supply point,turnover warehouse and demand point.
genetic annealing algorithmwarehouse positioningchromosome codingpower grid supply chainsupply and de-mand distribution of warehouse materialsfitness evolution
万方数据
维普
