A Tightened Formulation for Job Shop Scheduling with Mobile Robots

Abstract

In modern manufacturing, meeting the rising demand for customized products within tight deadlines poses significant challenges. Industry 4.0 offers opportunities to revolutionize manufacturing through automation, including adopting autonomous mobile robots. Integrating mobile robots into job shops introduces additional complexities, such as robot assignment and travel times, expanding the classical scheduling problem. In this paper, a mixed integer linear programming formulation is established to efficiently schedule mobile robots in smart job shops for on-time deliveries. It incorporates constraints on robot assignment and travel times alongside traditional machine and part-related constraints. To tackle the complexity of the problem, a systematic approach is employed to tighten the formulation, establishing linear relationships between operation and transportation sequence variables. Testing results demonstrate the effectiveness of the model and tightened constraints in achieving near-optimal solutions to meet on-time deliveries.