Research On Bi-Objective Batch Scheduling Processing Considering Differentiated Energy Consumption Of Parallel Machines

Production scheduling problem is a kind of important combinatorial optimization problem,which is widely used in many practical fields,such as from the typical large-scale semiconductor integrated chip production process of high-temperature testing links to port cargo handling,multistage lock scheduling,logistics and transportation,aviation industry and other fields.Unlike the classical scheduling problem,the machine can only process one job at a time,and in batch scheduling problem,the batch machine may process multiple jobs at the same time.It can be seen that the batch scheduling problem is more complicated than the classic scheduling problem,and it is more difficult to solve,but the research of batch machine scheduling problem is of great significance to improve the efficiency of resource utilization and productivity.Because of the complexity of the new problems,it is usually studied from the simple single machine processing environment,and the research on the single machine problem is helpful for us to solve the more complicated scheduling problem.In addition,with the concept of green manufacturing,parallel batch machine scheduling considering energy-saving objectives is an urgent scientific problem,and the current research results are few.So this dissertation is to consider the bi-objective energy-saving batch scheduling algorithm considering machine energy consumption.Firstly,this dissertation introduces the background of production scheduling problem,the related concepts and classification of scheduling problem,and then introduces the research status of processing environment and energy consumption in batch scheduling.Next,this dissertation will introduce the algorithm of solving batch scheduling problem,including deterministic algorithm and approximate algorithm.Then the characteristics of these two kinds of algorithms are briefly analyzed,and the general frame and the main algorithm are described.Then,according to the dynamic arrival of job,the optimization objective is to minimize the makespan and machine total energy consumption of parallel batch machine scheduling problem.First,the mathematical model of the problem is established,and an efficient ant colony optimization Algorithm(BOACO)is proposed to solve the problem.By analyzing the feature of the problem,the candidate set strategy is used to construct the solution in order to reduce the search space.At the same time,the relationship between the waste space and the problem objective is analyzed,and the heuristic information is defined based on waste space.In addition,to improve the quality of the solution,two effective local optimization strategies are proposed to optimize the solution for two different optimization objectives.Finally,-a complete algorithm description for the Ant colony optimization Algorithm(BOACO)are presented.In order to verify the performance of the proposed algorithm,the simulation experiments are compared with other existing algorithms in terms of quality,diversity and time performance.The results show that the proposed algorithm is superior to several other multi-objective evolutionary algorithms in the coverage,hypervolume and other evaluation metrics.Finally,the dissertation sums up the problem of batch scheduling for energy-saving bi-objective parallel machine and the proposed algorithm,and briefly introduces the future research direction of batch scheduling problem.