Migrating Birds Optimization Algorithm For Hybrid Flowshop Scheduling Problem With Lot-streaming

Lot-streaming(LS)is an effective method to improve production efficiency,which can shorten the idle time of the machine,reduce the accumulation of jobs,and speed up the processing speed of jobs.Hybrid flowshop scheduling(HFS)problem is mostly applied to the production process of multi-variety and small-scale production enterprises.Different from the traditional HFS problem,the hybrid flowshop scheduling with lot-streaming(HLFS)problem not only need to consider the processing sequence of jobs and how to reasonably allocate raw materials,but also need to consider how to properly divide the jobs.Therefore,the HLFS problem is more complicated than the HFS problem,and it is more difficult to optimize the problem.Based on the HLFS problem,it is more difficult to consider dynamic constraints and optimize it.During recent years,many kinds of meta-heuristic algorithms based on various biological behaviors and physical phenomena in nature have been proposed.It provides new ideas for the research of production scheduling problems.Migrating birds optimization(MBO)algorithm is a novel and efficient meta-heuristic algorithm that based on neighborhood search technology.This algorithm has the characteristics of simple structure,high robustness,and good convergence.Therefore,it has received the research and attention of many experts and scholars.The MBO algorithm is optimized by simulating a V-shaped formation to reduce energy loss during migrating birds.According to the characteristics of the HLFS problem,this paper uses a permuted encoding method.In order to reasonably arrange the jobs that reach the next stage at the same time,the shortest waiting time(SWT)rule is introduced.In order to ensure the quality and convergence speed of the algorithm,the mixed neighborhood of the individual is constructed by insertion,exchange and greedy algorithms.And then a local search method is designed to enhance the local search ability of the algorithm.In addition,a reset mechanism is added to avoid falling into local optimum.The numerical experiments prove that the proposed algorithm is more effectively.In addition,this paper considers the dynamic constraints in actual production scheduling.In order to solve the problem of hybrid flowshop scheduling with lot-streaming of random breakdown(RBHLFS)in a dynamic environment.The breakdown of the machine is divided into two cases,one is to continue processing after the breakdown of the machine,and the other is to restart processing after the breakdown of the machine.This paper analyzes the solutions to the breakdown of the machine at different times in detail,and proposes an improved migratory bird optimization algorithm for RBHLFS problem.The numerical experiments prove that the proposed algorithm is more effectively in the two cases.