Cat Swarm Optimization For Complex Flowshop Scheduling Problem

Production scheduling problems experienced decades of study and exploration gradually formed a mature theory,and generally applied to manufacturing enterprises,their theoretical research results also extend to Social services,Logistic,Informatization,Supply chain etc.Gantt was the first person who proposed scheduling problem in 1916,but in the ensuing decades keep slow development until 1954,Johnson conducted process of scheduling problems based on two machines,and then production scheduling problem begun step into the right track.Flow-shop scheduling problem is a kind of simplified model of reality production scheduling,which has been proved to be a kind of typical NP-hard problem[1],actually it's a kind of combinatorial optimization problems.The theory has been widely used in process industries and discrete manufacturing industry,which also has theoretical and practical value.First,the paper briefly reviews the relevant background knowledge production scheduling and research status,and introduced algorithms used to solve such problems,including various types of scheduling problems,especially Cat Swarm Optimization(CSO).Meanwhile,scheduling optimization problems and its theoretical system has been introduced in detail,and also introduced the traditional solutions and heuristic solution.Then,the basic theory of algorithm is the most important part in this article,the theory including framework of intelligent groups algorithm,and important parameters with related background knowledge of CSO,some improvement attempts have been made based on this,such as the improvement of the parameters and the introduction of quantum computing,which has greatly improved the algorithm search mechanism and the search efficiency of algorithm.In addition,this paper also further studied the flow-shop scheduling problem with learning effect,which more likely to be realistic problem,the experiment obtained effect of scheduling scheme under different circumstances by programming the simulation.Finally,in order verify the efficiency of the algorithm,the paper using Matlab programming simulation.