Abstarct: In this research, scheduling and inverse scheduling problems have been studied, today the importance of scheduling problems is clear in industry, commercial and in some cases in human resources (for example scheduling in hospitals or educational centers). Scheduling is necessary in most of organizations, offices and factories. A good scheduling can reduce the costs and increase the productivity. Higher competitive atmosphere for producers is also caused by effective scheduling. The main aim of scheduling is to balance different objectives; effective implementation of workers, equipment and facilities while reducing customer waiting time and processes time. This thesis will study inverse scheduling problems. Assume the production process requires some preparations which producer could provide them before producing and then choose the best sequence baxsed on disposal information. It is possible that jobs which enter after process have different characteristics and therefore, chosen permutation is not optimal anymore or sudden change may occur in product process. If the permutation is not able to change, like high cost of workstations movement, because of some reasons such as technology limitation, then producer need to adjust the speed which is actually process time adjustment. The high cost of these settings could become minimal by the use of inverse scheduling problems. In what follows, it will become clear that inverse scheduling problems can transform to linear programming problems even on issues that scheduling problem could not be solved in polynomial time complexity. Inverse optimization is practical in many issues such as geophysical sciences, medical imaging, traffic issues and other applications. The main use of inverse scheduling problems is in a condition that parameters can be set between productive and customers. The main job parameters are those that customers prefer and their corresponding error values, is one that productive manager offer. Another application of inverse scheduling problems could be in trail job systems with a control over the parameters. In particular, the one who do the scheduling in these systems, obtain some information after job parameters enter to the system. Scheduler can adjust the actual amount of parameters with customers, to ensure that even after the new parameters were added to the optimal timing, the system remain optimized. The use of inverse scheduling problems, determines the least amount of change in the job parameters.