The Research On The Export And Storage Of Warehouse And Production Scheduling Of Aluminum Industrial

Aluminum industry can provide important raw materials for the economy production and life of the national.With the development of the economics of our country,the requirements for the quality and production efficiency of aluminum industry products are getting much higher,as a result,we have to do some research for the optimization of logistics and production scheduling in aluminum production.At present,automated warehouse has been widely used in aluminum production enterprises,and as a new and efficient warehousing structure,warehouse can not only save storage costs,but also improve the efficiency of storage and delivery of the aluminum production,furthermore,it can also improve the economic efficiency of enterprises.Aluminum production process has many varieties of small batch features,so that it can be attributed to the job shop scheduling problem,as a result,we have the need to study its optimization algorithm.In this thesis,logistics scheduling and production scheduling of the aluminum industry are studied.In terms of logistics scheduling,we aim at the problem of warehouse dispatching during the storage of aluminum profiles,and study the path planning modeling and optimization algorithm of the stacker.In terms of production scheduling,we study the optimization algorithm of job shop scheduling problem in industrial manufacturing system.Specific research includes:1)To solve the problem of the operation path planning of stacker in automated warehouse,the paper analyzes the operation path of stacker,and aims to minimize the completion time under the constraints of space constraints,cargo position constraints and the operation constraints of stacker.Then we establish the integer programming model and solve the model by CPLEX software.The result verifies the correctness and validity of the model.2)Combined with the characteristics of stacker running path,a learning strategy based improved discrete differential evolution algorithm is proposed to solve the problem.In order to maintain the diversity of the population,a greedy algorithm and a stochastic mechanism are used to generate the initial population.In the iterative process,a variable neighborhood search strategy is added to avoid the algorithm getting into the bureau superiority.Since the initial evolutionary result is not suitable for learning,the learning strategy is joined a little late.The experimental data from simulated production shows that the improvement of the proposed improved differential evolution algorithm is better than the basic discrete differential evolution before improvement,and the convergence speed is also obviously accelerated.Finally,the result is compared with the result of CPLEX,which verifies the effectiveness of the improved algorithm in solving the problem.3)To solve the job shop scheduling problem in aluminum industrial production,a hybrid algorithm of shifting bottleneck algorithm and differential evolution is proposed.To find out the bottleneck of shifting bottleneck algorithm,the differential evolution algorithm is used to solve the single machine problem.The bottleneck can be used in combination of the shifting bottleneck algorithm which exploit the problem structure and the differential evolution which has strong search ability.The results of the proposed algorithm are compared with those of the standard test.The results show that the hybrid algorithm can solve the job shop scheduling problem effectively.