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MILP and Heuristic approaches for task scheduling in robotic matrix-structured assembly system
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DOI：10.1080/17509653.2026.2655787.png)
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Abstract
En 中文
Assembly planning is a critical stage in manufacturing, accounting for up to 40–60% of production time and over 20% of costs. Although most studies on matrix-structure assembly systems focus on minimizing automated guided vehicle (AGV) trajectories, far less attention has been devoted to workstation utilization and task sequencing, both of which are essential for system profitability. This paper addresses the scheduling problem in robotic matrix-structure assembly systems (RMSAS) for multi-model production, where sequencing, task assignment, and workstation efficiency are strongly interdependent. Three approaches are evaluated: a Mixed-Integer Linear Programming (MILP) model, a math-heuristic (M-H) formulation, and a dispatching rule based on longest remaining processing time (LRPT). Results indicate that MILP guarantees optimality but suffers from scalability issues due to the NP-hard nature of the problem, while remaining a valuable benchmark. The M-H formulation achieves near-optimal solutions in a practical amount of time, significantly reducing computational effort. LRPT offers rapid scheduling but results in lower utilization and longer makespan. Overall, the M-H formulation stands out as a practical and efficient approach, advancing RMSAS scheduling beyond AGV path minimization toward enhanced workstation performance.
Keywords:
Matrix-structure assembly system
robotics assembly system
scheduling
C61
D24
L23
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2.6
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237
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739
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