Research On Distributed Replacement Assembly Workshop Scheduling Based On Improved Artificial Bee Colony Algorithm

In the context of the globalization of production,economic development is very rapid,the demand of customers is more and more diversified,and the scale of manufacturing enterprises is more and more huge.In order to improve production efficiency and reduce costs,many enterprises have begun to expand the traditional centralized production to distributed production and set up many factories.Distributed permutation flow shop scheduling problem(DPFSP),as a typical problem in shop scheduling,is also an extension of the permutation flow shop scheduling problem(PFSP),which also belongs to NP-hard problem.not only to carry out a reasonable processing sequence of workpieces,but also to weigh the distribution of workpieces to the factory,which is a combination optimization problem,which is very difficult to achieve the optimal goal.No-idle constraint is added on the basis of DPFSP.Studying NDPFSP can reduce the energy consumption generated by idle processing machines,better achieve energy saving and emission reduction,and further reduce production costs.Therefore,an improved artificial bee colony algorithm is proposed to solve the PFSP,the DPFSP and the NDPFSP.First of all,point out the background and meaning of this article,and the research status of PFSP,DPFSP,NDPFSP and artificial bee colony algorithm are summarized.Then,the basic artificial bee colony algorithm is briefly introduced,including the principle,characteristics and algorithm steps of the algorithm.Thirdly,this paper studies the problem of the PFSP,in order to solve this problem,the artificial bee colony algorithm is improved.and the idea of differential evolution algorithm is integrated into the employed bee’s stage,and Gaussian mutation operators are added to accelerate the convergence speed.In the onlooker bee’s stage,an adaptive strategy is added to balance the exploration and development capabilities of the algorithm;In the scout bee’s stage,add the Cauchy mutation operator to avoid falling into local extremes.Then the DPFSP is studied.In order to solve this problem,the artificial bee colony algorithm is improved.in the employed bees stage,first generate a random number,according to the size of the random value to decide to select the insertion operation or exchange operation(the insertion operation is divided into intra-factory insertion and inter-plant insertion,the exchange operation is divided into intra-factory exchange and inter-factory exchange),randomly select two factories,if the factory is the same,the intra-factory operation is adopted,if the factories are different,Inter-factory operation is used.In the onlooker bees’ stage,the onlooker bees first select the best food source according to the size of the fitness value,and then hires the food source found by the bee to perform a mutation operation with reference to the best food source to obtain a new food source,that is,the new solution.In the scout bees’ phase,use the same four modes of operation as the employed bee’s stage.Finally,the NDPFSP is studied,in order to solve this problem,the algorithm is further improved.And a disturbance operator is added in the employed bee’s stage,and the intra-factory exchange and intra-factory insertion operation are improved,the onlooker bees’ stage is consistent with the algorithm proposed by DPFSP,and the same four operation methods are used in the reconnaissance bee stage and the employed bee’s stage.For different scheduling problems,simulation tests are carried out by using various scale examples,and the test results are analyzed to verify the effectiveness and superiority of the proposed algorithm.