Research On Lot Streaming Flexible Job Shop Scheduling Problem Based On Artificial Bee Colony Algorithm

Lot streaming flexible job shop scheduling problem(LSFJSP)comes from flexible job shop scheduling problem(FJSP).It is a method to deal with batch flow,which is more suitable for the multi variety medium batch production mode of actual enterprises.It has important research and application value.In this paper,when we study the LSFJSP problem,we consider the LSFJSP of consistent batch,LSFJSP of inconsistent batch and LSFJSP of multi-objective respectively,and design an improved artificial bee colony algorithm(IABC)to solve the above problem.Firstly,Lot streaming flexible job shop scheduling problem is described in detail.Four different LSFJSP batching modes and their overlap characteristics are introduced.The basic theory and algorithm flow of artificial bee colony algorithm are introduced to show the core solution method of this paper.The basic framework of solving lot streaming flexible job shop scheduling problem with improved artificial bee colony algorithm is described.Aiming at the equal consistent LSFJSP(ECLS＿FJSP),the EC-ABC algorithm is designed to solve the problem.Firstly,mathematical model of ECLS＿FJSP with the goal of minimizing maximum completion time is established.Then,according to the discrete characteristics of ECLS＿FJSP,a double-layer coding method,an appropriate initialization strategy and a population evolution guidance scheme are designed,and Levy flight is used for global search.Finally,compared with the data experiments of other algorithms,it is verified that EC-ABC has a great improvement in convergence speed and solution effect.Aiming at the equal inconsistent LSFJSP(EILS＿FJSP),the EI-ABC algorithm is designed to solve the problem.Firstly,mathematical model of EILS＿FJSP with the goal of minimizing maximum completion time is established.Then,a two-layer coding scheme is designed to describe the problem,and an efficient inconsistent batch active decoding scheme,bee colony communication guidance mechanism and sub batch binary detection method are proposed to improve the search ability of the algorithm.Finally,compared with the data experiments of other algorithms,EI-ABC shows faster convergence speed and better solution effect.Aiming at the multi-objective production scheduling problem of LSFJSP,the MOABC algorithm is designed to solve it.Firstly,considering the two optimization objectives of minimizing maximum completion time and minimizing maximum machine load,a mathematical model is established.Then,based on IABC and Pareto optimization theory,the local search ability is improved by introducing elitist retention strategy,non dominated sorting strategy and crowding distance algorithm,and a small population cross guidance mechanism under multi-level dominance level is designed to improve the performance of the algorithm.Finally,compared with other algorithms,MOABC has obvious advantages in convergence speed and solution effect.Finally,This paper summarizes the main research work of LSFJSP,and prospects the future research direction.