Research On Optimization Of Multisequence Finite Buffer In Flexible Flow Shop With Setup Time  Posted on:20190404  Degree:Master  Type:Thesis  Country:China  Candidate:F Meng  Full Text:PDF  GTID:2428330545455843  Subject:Control theory and control engineering  Abstract/Summary:  PDF Full Text Request  The optimization of multisequence finite buffer in the flexible flow shop with setup time is an extension of the classical flexible flow shop problem in the flexible flow shop,it takes into account the impact of station setup time and multisequence finite buffering on production and processing.Flexible flow shop with multistation and multiprocess characteristics,it is a kind of NPHard problem,which is widespread in the steel production,vehicle manufacturing,semiconductor packaging and other industries in the production enterprises.In the theoretical study,it is assumed that there is no time to be prepared in the work station and the capacity of the buffer is infinite,but the actual manufacturing enterprises are limited by the diversity of workshop resources and production products.There are many sequences of limited buffer and station setup time in the production process.The work station setup time is influenced by various types of attribute information such as the type,color and shape of the object to be processed.The multisequence finite buffers is composed of multiple processing sequences,not only to consider the capacity of each sequence in the buffer,but also to consider the assignment of the workpiece into multiple sequence buffers.And the workpiece buffer area is limited by the station setup time.This type of production workshop has such characteristics,the process is complex,the production links are limited,which put forward higher requirements.At present,it is difficult to find a more effective solution to solve these problems,resulting in the results of the production can not be a good guide to the production process of such workshops.Therefore,it is of great theoretical and practical value to study the scheduling problem of multisequence finite buffer in the flexible flow shop with setup time.In this paper,a mathematical programming model is established to solve the scheduling problem of multisequence finite buffer in flexible flow shop with setup time.The improved algorithm based on the whale optimization algorithm is combined with the initial population establishment method based on the optimization target,it is taken as the global optimization method.And the global optimization algorithm and the local assignment rule are combined to solve the optimization of the problem of flexible flow shop with setup time,and through experiments to verify the effectiveness.The main contents of this paper are as follows:(1)Establish mathematical programming model of scheduling optimization problem with multisequence finite buffer in flexible flow shop with setup time.The classical flexible flow shop mathematic planning model is added with the station of setup the time model element and the sequence finite element model element.And the mathematical model of multisequence finite buffer and station setup time is established.(2)Whale optimization algorithm.As a novel primitive heuristic algorithm based on group class,WOA algorithm is simple and easy to use.It is an optimization algorithm with short optimization time and fast convergence in the search space to the optimal solution.The WOA algorithm can give full play to its advantages in solving the problem of arranging optimization of the flexible buffer shop in the complex finite buffer area.It can solve these complex problems quickly.Therefore,in this paper,the WOA algorithm is used to solve the problem of multi－sequence finite buffer scheduling problem in the flexible flow shop with the setup time,and its validity and superiority are verified.(3)An Improved Method Based on WOA Algorithm.Due to the shortcomings of WOA algorithm,the fast convergence of WOA algorithm,easy to fall into the local extremum and decrease the diversity of the late stage of evolution,this paper improves the algorithm by using three methods.And then,an improved whale optimization algorithm(SLO WOA)is proposed.And verify the validity of the simulation by comparing the simulation examples and the comparative analysis.Improvements are as follow:①In the search process,Levy flight search strategy is used to expand the search range of the whale optimization algorithm while making it more powerful in the local scope.②In the process of individual renewal,the idea of simulated annealing is used to accept the new individual with a certain probability to keep the diversity of the population in the update.③In the later stages of population evolution,population diversity was reduced.in order to improve group diversity,reverse learning strategies is used.(4)Research on Initial Population Establishment Method Based on Optimization Target.An ISLOWOA algorithm(It is a method composed with optimize the initial population establishment method and the improved whale optimization algorithm(SLOWOA),which can improve the efficiency of SLOWOA algorithm to search the optimal solution)based on the initial population establishment method is proposed to improve the quality of the initial solution in the initial population and to speed up the optimization of the algorithm.And verify the validity of the simulation by comparing the simulation examples and the comparative analysis.(5)Research on Local Assignment Rule Method.When the workpiece enters the buffer zone,the maximum sequence buffer remaining capacity priority rule is used as the highest priority rule to control the waiting queue allocation process of the workpiece in multiple buffers.Out of the buffer zone,according to the firstin firstout rule to control the workpiece out of the buffer zone.The station chooses to process the workpiece with the minimum setup time as the highest priority rule to minimize the impact of the setup time on the scheduling process.At the same time,the global optimization algorithm is combined with the local assignment rule as a method to solve the problem of flexible flow shop scheduling optimization of multisequence finitebuffers with setup time.  Keywords/Search Tags:  Setup time, Multisequence finite buffer, Whale optimization algorithm, Levy flight, Simulated annealing, Reverse learning, Local assignment rules, Initial population construction  PDF Full Text Request  Related items 
 
