Research On PSO-based Technique Of Buffer Capacity Allocation Of Serial Line Manufacture System

With the development of the modern market,thecooperation of internal enterprise and between enterprises for manufacturing become increasingly frequent,which constitute a network of interconnected system.Pursuit of overall system optimal or win-win situation is the key thatenterprise win the survival in the market of development and competition.Buffer is designed to be a temporary storage for semi-finished products,finished productsto reduce the performance or damage from the adverse state of system to the performance of other system unit even the whole system,which is in relation to the whole efficiency of the manufacturing system and success.In terms of the modern market environment,buffer cannot be cancelledwhether from the perspective of supply chain logistics or internal of actual production needs in modern market environment.In the past,production imbalance and even business failure will be meet for lacking of mature theoretical guidance and largely dependenting on the experience,when enterpriseis in the buffer capacity assignment.Modern enterprise urgently need to solve howto allocate buffer capacity of manufacturing systems from the perspective of system as a wholefrom the theoretical basis in the situation that factors of production is disturbed by random eventsin order to achieve the purpose of reduce the cost and the overall optimal.Forserial line disturbed by random events,the study deal with buffer capacity allocation problem with anobjective of maximum productivity for a buffer capacity fixed.The main research results are as follows:(1)For serial line,researching on the system performance analysis techniques such as the decomposition method and the comprehensive method,mastering the idea and program algorithm,learningthe advantages and disadvantages through the numerical simulation experiment,laying a foundation for solving the problem of optimal allocation of buffer capacity performance analysis technology.(2)A modified multiple population particle swarm optimization is put forward combined with decomposition method.It is different from the traditional particle swarm optimization algorithm which is search by only a single group.The method putting a certain size of particle swarm into several species,respectively according to the strategies of the inertia weight for rules of linear decreasing,and attaching different inertia weight to various group,solve the buffer capacity optimization allocation problemfor serial line.In comparison with the traditional classic modifiedparticle swarm algorithm,experiment shows that the advantages and disadvantages of the algorithm.(3)Further,a gaussian chaotic mutation-adaptive particle swarm optimization is put forward combined with decomposition method,based on the above research,for the shortcomings that modified multiple population particle swarm optimizationhave slow convergence and long operation time.The algorithm using the diversity measure function as feedback strategy to adjust inertia weight by themselves to achieve high convergence rate,disturbing the algorithm by using the gaussian chaotic mutation to make it jump out of local optimum,solve the buffer capacity optimization allocation problemfor serial linepreferably.Experiments verify the validity and superiority of the algorithm in comparison with the modified multiple population particle swarm optimization and traditional algorithm of particle swarm optimization.(4)Finally,a " serial line buffer capacity allocation" software tools is developed based on MATLAB GUI graphical user interface combined with the above algorithmfrom the practical perspective,developed,laying a foundation for a more general hybrid manufacturing system software module development.