A study about job-shop scheduling with the help of genetic algorithms

One of the main important goals in groving economics is to minimize manufactoring process of product and to fulfill appropriately desired time of customer demand. In manufactoring systems that there are multiple orders , different methods and approaches are used to solve the problems that schedule in machine- job installation.The job shop schedulings located in class of the hard problem(NP). Complete solution values of these problems can not be obtained with conventional methods. In the shops consisting of more than one (N) machines, heuristic mesthods are used to solve scheduling problems. One of these heuristic methods is Genetic Algorithms (GA). In this thesis, in the job shop schedulings that are a type of scheduling problems, three different studies that use Genetic Algorithm (GA) of the heuristics methods are searched to be completed in orders as soon as possible. Each of these three studies is ajob shop scheduling problem and they are solved with the different methods of GA. In this studies, comparasioans between results of GA and results of classic scheduling method are researched. Studies between in commons and differents have commented.A result of this thesis, results that are obtained in different sectors with different methods of GA, different genetic operators and different conjectures are compared.