| With the rapid development of science,the improvement of people’s material living standard has promoted the transformation of consumption demand and consumption pattern.For manufacturing enterprises,the production mode of separating production and distribution has been difficult to meet the increasingly rapid and diversified needs of customers,so how to ration ally allocate resources in the supply chain system has become the key for enterprises to improve efficiency and competitiveness.The integrated scheduling of production and distribution aims to combine the processing and delivery of orders,and then shorten the delivery cycle of orders to meet the demand of rapid consumption.Therefore,this paper studies the problem of distributed production and distribution integrated scheduling based on worker factors and logistics mode.(1)In view of the traditional integrated scheduling problem of production and distribution,factors such as worker constraints and distributed factories are not considered,this paper studies the integrated model of distributed production and distribution under worker constraints.Before order processing,a group of multi-skilled workers are required to complete preparatory activities,and workers can be transferred between machines.To solve this problem,a mixed integer linear programming model(MILP)is established to minimize the total cost of the enterprise.By integrating swarm intelligence algorithm and search algorithm,this paper designs an improved meme algorithm to solve the problem.The algorithm proposes seven domain operators and a new population updating method to accelerate th e convergence speed.In order to verify the performance of the algorithm,72 examples are constructed.Taguchi method was used to select the optimal parameter combination for the three parameters of the algorithm: population decline rate,crossover probabili ty and mutation probability.Comparing the algorithm with CPLEX solver,the advantages of the algorithm on small-scale problems are obtained.Experimental results show that the proposed algorithm is superior to genetic algorithm,improved genetic algorithm and simulated annealing algorithm.(2)In view of the punctuality of enterprise logistics and the economy of third-party logistics,this paper considers the integrated model of distributed production and distribution under the mixed logistics mode.The deli very task of the order is completed by self-operated fleet and third-party logistics enterprises with different transportation costs.An efficient meme algorithm is proposed to solve the problem.Using real number coding instead of integer coding simplifies the representation of chromosomes and facilitates the operation of chromosomes.For the initial solution and decoding method,combined with the characteristics of the model,a variety of heuristic rules are used to select better individuals.In addition,the algorithm also improves the local search part and adaptively selects the domain operator to accelerate the convergence speed.In order to verify the effectiveness of the improved algorithm on the model,a full-factor experiment is carried out on the algorithm,and then four parameters of the algorithm,including population decline rate,population size,crossover probability and mutation probability,are determined.Simulation results show that the algorithm is superior to CPLEX exact solver in solving efficiency.Furthermore,compared with genetic algorithm,improved genetic algorithm,simulated annealing algorithm and large domain search algorithm,the superiority of the algorithm is proved.In addition,according to the characteristics of the model,this pap er also discusses the upper limit of the model,time interval,logistics cost and other factors,the experiment shows that these factors play a decisive role in the choice of logistics mode and logistics cost. |
