Minimising makespan in distributed mixed no-idle flowshops
研究了分布式混合无空闲流水车间调度问题，以最小化完工时间为目标，提出了一种基于云理论的迭代贪婪算法，实验表明该算法优于经典方法。
The rapid growth of distributed manufacturing in industry today has recently attracted significant research attention that has focused on distributed scheduling problems. This work studied the distributed mixed no-idle flowshop scheduling problem using makespan as an optimality criterion. To the best of the authors’ knowledge, this is the first paper to study the multi-flowshop extension in which each flowshop has mixed no-idle constraints. A novel cloud theory-based iterated greedy (CTBIG) algorithm was proposed for solving the problem. Computational experiments conducted on a set of test instances revealed that the proposed CTBIG algorithm significantly outperformed classic iterated greedy algorithms.