Research On The Fuzzy Job Shop Scheduling Problem Based On Adaptive Genetic And Cloning Algorithm

In the industrial production, every production system is used to solve the problem ofproduction planning and scheduling. The shop scheduling was conducted during the workshopproduction scheduling, which is the core of the production of manufacturing automation,information, and intelligent. The Job-Shop Scheduling Problems (JSSP) is a typical combinatorialoptimization problem. Based on the problem, this paper described the fuzzy JSSP. And researchthe fuzzy JSSP based on the genetic clonal selection algorithm. Then design the mathematicalmodel and the solving algorithm. The main contents are as follows:At first, analyses the research situation of the workshop scheduling problem. Then discussesthe basic idea, basic elements, algorithm process of genetic algorithm and clonal selectionalgorithm, the adaptive genetic operation and clone operation and so on. Then combine the geneticalgorithm with clonal selection algorithm. The paper proposed two improved algorithm which arethe adaptive genetic clonal selection algorithm (AGACA) and the adaptive genetic clonal selectionalgorithm with memory module (AGACA_M). A larger number of JSSP problems have beentested, and the experimental results demonstrate the effectiveness of the algorithm and verify theeffectiveness of the adaptive genetic clonal selection mechanism for the algorithm to choice thegood solution. Moreover, prove the memory module is good for the algorithm to preserve theoptimal solution and keep the diversity of the population.