Some heuristic to solve job shop machine scheduling problems

Presenting a comparatively easy and efficient approach to scheduling issues is the goal of this study. In this study, a novel heuristic approach for workshop scheduling issues has been created and presented with the goal of lowering completion time. A mixture of dispatching rules, including "earliest deadline" for each work, "shortest processing time" for each task, "least tardiness" for the operations in each sequence, and the notion of "first-come, first-served," form the basis of the evaluation. Additionally, in contrast to the majority of heuristic algorithms, the user-specified deadline for each task is taken into consideration while determining the best timetable. This suggested approach has been used to schedule a series of JSP tasks with various properties. One of the most popular and trustworthy heuristic techniques, the shifting bottleneck algorithm, was also applied to solve the models. The results of the output comparison demonstrate the superiority of the suggested algorithm by achieving a substantially shorter and better time period when the number of jobs is less than or equal to the number of machines. Furthermore, the suggested approach produces more efficient results when the ratio of jobs to machines is smaller than 2.1 for the category where the number of jobs exceeds the number of machines. However, when the aforementioned ratio surpasses 2.1, a shorter completion time may be attained by any approach in this category. Since the data do not exhibit any particular pattern, it is not possible to make broad generalizations in this instance.