A novel real-world human-robot collaboration scheduling problem: a combination of assembly line balancing and flow shop scheduling

Nowadays, numerous manufacturing companies are striving to enhance their process performance by leveraging innovative technologies like collaborative robots. This paper introduces a novel Human-Robot Collaboration (HRC) scheduling problem, motivated by an industry-university partnership project. For simplicity, this scheduling problem is named “ALB-HRC-FSS”, as it combines elements of the traditional Assembly Line Balancing (ALB) and Flow Shop Scheduling (FSS) problems while incorporating the concurrent use of human workers and collaborative robots. As far as we know, this study is among the first to link the ALB-HRC with the FSS from a mathematical standpoint. A detailed description of the proposed ALB-HRC-FSS problem setting is presented by numerical examples, disjunctive graphs and Gantt charts. A series of Mixed-Integer Programming (MIP) models are developed to formulate the problem interactively. Due to computational complexity, a hybrid metaheuristic algorithm (i.e., a combination of Memetic Algorithm and Tabu Search) is developed to solve the ALB-HRC-FSS problem effectively. Computational experiments with scenario-based analysis are performed to verify the practicality and effectiveness of the proposed ALB-HRC-FSS methodology. As the ALB-HRC-FSS integrates the strengths of three research domains (i.e., assembly line balancing, human-robot collaboration and flow shop scheduling), this study contributes to designing a more holistic industrial system for reshaping manufacturing processes in the context of Industry 5.0.