Application Research Of Batch Scheduling Problem On Multi-objective ACO Algorithms With Denial

Scheduling problem is an extremely special and diversified combinatorial optimization problem,which is widely used in all aspects of life,such as logistics,processing manufacturing,and so on.The main purpose of the research scheduling problem is to allocate the limited resources reasonably,so that the resources can be organized in the process of distribution to improve the production efficiency and bring more benefits to the enterprise.However,with the continuous expansion of production scale,the scheduling problem becomes more and more complex.In order to improve the business conditions of the enterprise,a new scheduling problem has emerged-batch processing scheduling,which can be referred to as batch scheduling.The main difference between the batch scheduling problem and the traditional classical scheduling problem is that at the same time,multiple jobs can be processed by the same machine at the same time,that is,multiple jobs are processed on the machine in batches,and the processing time is equal to the maximum processing time of all the jobs in the batch.Due to the influence of jobs attributes,machine attributes and objective functions,the problem of batch scheduling is very complicated,which proves to be a NP-hard problem even in a s single machine environment.In order to solve such problems,many domestic and foreign experts and scholars began to search for more efficient solutions.In addition,in order to reduce production time,enterprises must refuse to process certain jobs,therefore they have to pay a certain price,that is,there is a rejection cost.The research goal of this paper is to minimize the makespan of manufacturing and the total rejection cost.Firstly,the research background of batch scheduling problem is introduced and the relevant content in the three-parameter representation is described.Then this paper introduces the research status of batch scheduling problem,including single machine,multi-machine and batch scheduling problem with the rejection cost.Secondly,three kinds of algorithms for solving batch scheduling problems are introduced,which are deterministic algorithm,heuristic algorithm and meta-heuristic algorithm respectively.Thirdly,based on ant colony optimization(ACO)algorithm,two algorithms of LA CO and PACO are proposed to solve two multi-objective optimization problems of linear combination and Pareto-based non-dominated solution respectively.In addition,the common parts of LACO and PACO algorithm are introduced in detail,such as the definition of double pheromone matrix,the definition of double heuristic information and so on,as well as their different parts.Fourthly,the setting of parameters and the generation of test cases are described.Then,the experimental data are calculated.The experimental results obtained by the proposed algorithm are compared with those of other comparative algorithms,and the relevant conclusions are drawn.Finally,we summarize the research content of this article and make a prospect of future research.