Developing job flow time preduction models in the dynamic unbalanced job shop

This research addresses flow time preduction in the dynamic unbalanced job shop scheduling environment. The specific purpose of the research is to developo the job flow time prediction model in the dynamic unbalanced job shop. Such factors as job characteristics, job shop status, characteristics of the shop workload, shop dispatching rules, shop structure, etc. are considered in the model. The regression prediction approach is analyzed within a dynamic, make-to-order job shop simulation model. Mean Absolute Lateness and Mean Relative Error are used to compare and evaluate alternative regression models developed in this research.