A Discrete Artificial Bee Colony Algorithm For The No-idle/Distributed Permutation Flowshop Scheduling

It is multi-product and small-batch production model that promotes distributed manufacturing.Distributed manufacturing can make full use of the resources of companies or factories from place to place to produce more quickly at lower cost.The distributed permutation flowshop scheduling problem belongs to distributed manufacturing,and it mainly deals with how to assign jobs to factories and determine the processing sequence of the jobs in each factory to achieve the optimal goal.In theory,the distributed permutation flowshop scheduling problem is also a NP-hard problem,which is difficult to solve.In practical production,solving this problem definitely can reduce production costs and improve efficiency.Therefore,the study of distributed permutation flowshop scheduling problem is of great significance.First of all,the background and significance of this paper are pointed out.Then,the domestic and overseas research status of permutation flowshop scheduling problem,no-idle/distributed permutation flowshop scheduling problem and Artificial Bee Colony algorithm are briefly summarized in the paper.Secondly,an introduction to the principle and process of Artificial Bee Colony algorithm is simply analysed in this article.Thirdly,on the basis of introducing the permutation flow shop scheduling problem,the distributed permutation flowshop scheduling problem is further studied.Aimed at solving the issues discussed above with minimizing the completion time,new mathematical models are established and solutions to getC_maxare given respectively and a Discrete Artificial Bee Colony algorithm is designed.This method is mainly to improve the efficiency of local search in three stages including employed bees,onlooker bees and scout bees.In the first stage,randomly select one method among exter-factory insert,exter-factory swap,inter-factory swap and perform a neighborhood search to generate a new solution in the existing solution space.In the following second stage,the solution is improved using a local search strategy based on critical factory to enhance local search capabilities.Then,in the last stage,three operations are used in turn.In addition to this,a method based on variable neighborhood descent is also designed.Lastly,the no-idle distributed permutation flowshop scheduling problem is further studied.To minimize the completion time,new mathematical models are established and solutions to get C_maxare given respectively.On the basis of the algorithm mentioned above,the method in second stage is improved.Simulations for small-scale and large-scale instances demonstrate the effectiveness of the given Discrete Artificial Bee Colony algorithm in solving no-idle/distributed permutation flowshop scheduling problems.