An Efficient Iterative Beam Search for Human–Robot Collaborative Assembly Line Balancing

Modern cyber–physical systems (CPSs) and IoT-enabled smart factories rely on human–robot collaboration (HRC) to combine human intuition and robotic precision in real time. Balancing such HRC assembly lines, where each task may execute in human-only, robot-only, or collaborative modes, poses a combinatorial challenge that defies scalable mixed integer linear programming (MILP) and oversimplified heuristics. In this letter, we present IBSHRC, a proof-of-concept Iterative Beam Search framework designed for single-product, straight-line CPS assembly systems. IBSHRC leverages mode-aware initialization, binary-search cycle-time refinement, and efficient pruning to navigate vast scheduling spaces at the network edge. On benchmark instances up to 100 tasks, our method delivers near-optimal cycle times with up to $300\times $ speed-ups over MILP (subsecond runtimes), demonstrating its promise for real-time, IoT-driven industrial scheduling.