Local search based meta-heuristic algorithms for optimizing the cyclic flexible manufacturing cell problem

Flexible robotic cells are used in many real-life industries to produce standardized items at a high production speed. These cells use high-tech and expensive machines. Determining the schedules of these cells for the most efficient usage arises as an important optimization problem in those industries. In this study, the scheduling problem of a flexible robotic cell is considered. Machines are identical and parallel. In the cell, there is an input and an output buffer wherein items being processed and the finished items are kept, respectively. There is a robot performing the loading/unloading operations of the machines and transporting the items. The system repeats a cycle in its run. It is assumed that each machine processes one part in each cycle. The cycle time depends on the order of the loading/unloading activities. Therefore, determining the order of these activities for the minimum cycle time is needed. We propose a new mathematical model to solve the problem. For large size problems, three metaheuristic algorithms based on local search algorithm are proposed. In the metaheuristics, in order to compute the minimum cycle time of a given solution a linear programming model is needed to be solved which is one of the recent cases in the literature to the best of our knowledge. Several numerical examples are solved by the proposed algorithms and their performance and solutions are compared.