Studies On Job-Shop Scheduling Problems Based On Genetic Algorithms

The article mainly uses hybrid genetic algorithms as tool to study the static and dynamic scheduling of job shop.To the static and dynamic scheduling problem of framework,mathematical models and strategies are established,determine the workpiece to be shortest production cycle as the optimization goal.Introduces the basic concept?basic operation process of genetic algorithm and genetic operation.In view of the specific case,determine the encoding and decoding scheme,design the genetic operators and parameters of the algorithm.Finally,to the case analysis,static and dynamic scheduling software is developed using MATLAB.The best strategy and target value are pointed out.The principal research results and contents can be outlined as following:(1)The static scheduling problem,this dissertation made detailed mathematical,determine the encoding and decoding scheme,with the algorithm design of genetic operator and the corresponding parameters,finally,through the MATLAB simulation software to optimize the solution of the static scheduling problem optimal value and optimal scheduling scheme,the best strategy is pointed out.(2)Based on the above static scheduling,study of the dynamic scheduling problem of dynamic events,established the mathematical model for the dynamic scheduling,the optimization goal is determined.Determining the encoding and decoding scheme,new initial population strategies and genetic operators are studied and analyzed.Finally,through the MATLAB simulation software to optimize the best optimal values and the corresponding optimal scheduling scheme.(3)The above results by MATLAB,finally in the MATLAB to carry on the secondary development,optimize the management and operation of static and dynamic scheduling problem of solution convergence graph and scheduling Gantt chart.