SCHEDULING AUTONOMOUS MOBILE ROBOTS IN FLEXIBLE MANUFACTURING ENVIRONMENT USING NEIGHBORHOOD SEARCH METAHEURISTICS

The pursuit of increased efficiency in large-scale automated production systems, particularly in cases where manual process adaptability is possible, has prompted companies to embrace automation technologies and autonomous mobile robots (AMRs). Companies are adopting flexible manufacturing systems (FMS) in conjunction with AMRs to handle complex or repetitive tasks, such as material transportation and performing of manufacturing operations. In this context, the problem addressed in this paper is the scheduling of tasks to AMRs in a flexible manufacturing environment.The robots are responsible for supplying machine feeders to prevent interruptions in operations caused by a shortage of parts. A mixed-integer linear programming model is proposed to achieve optimal solutions for small instances of the problem, with the objective of minimizing the makespan. The problem is classified as NP-Hard, and two computational methods based on Variable Neighborhood Search and Variable Neighborhood Descent metaheuristics were presented. Computational experiments are also conducted, and the results indicate that the proposed approach can be successfully applied to more complex examples.