ABSTRACT
The job shop environment has been studied extensively for many decades. Wide and diverse algorithms have been proposed with different characteristics. Most approaches, for solving the job shop environment, consider the scheduling and process planning as independent events. Modelling the interactions between scheduling and process planning is the goal of this research. In this study, an estimation of distribution algorithm, proposed by Mühlenbein and Paaß, is used to identify interactions between variables of the problem. The relevance of this paper is validated by a comparison of the results with other algorithms on certain general and standard benchmarking datasets. The solution representation used in this study is suitable for implementing probability models. The proposed algorithm offers a better estimation of each operation in the machine assignment for the job shop environment.
