The independent consideration of production lot-sizing and scheduling decisions may lead to infeasible production plans, an increase in costs, and inadequate use of resources. This work analyzes different forms of connection between these two problems. We propose iterative strategies to solve lot-sizing and scheduling problems in cases of infeasibilities, comparing the results with integrated and hierarchical approaches. For the integrated approach, we use a continuous formulation with a warm-start. For the hierarchical approach, we implement three different strategies based on literature studies. This paper focuses on the diverse information shared between the decision levels of the hierarchical and iterative methods. We propose a comprehensive benchmark considering Uniform, Normal, and Poisson distributions, with three different scenarios. Results show the efficiency of the hierarchical and iterative strategies, finding good quality solutions in short computational times. Therefore, they are effective alternatives for problems considering the combination of production lot-sizing and scheduling, especially when considering large instances.

对生产批量大小和计划决策的独立考虑可能导致不可行的生产计划，成本增加以及资源使用不足。这项工作分析了这两个问题之间的不同形式的联系。我们提出了迭代策略来解决不可行情况下的批量和计划问题，并将结果与​​集成和分层方法进行比较。对于集成方法，我们使用热启动的连续公式。对于分层方法，我们基于文献研究实施了三种不同的策略。本文着眼于分层方法和迭代方法的决策层之间共享的各种信息。我们提出了一种综合基准，其中考虑了三种情况下的均匀分布，正态分布和泊松分布。结果显示了分层和迭代策略的效率，可以在较短的计算时间内找到高质量的解决方案。因此，它们是考虑生产批量和计划安排相结合的问题的有效替代方法，尤其是在考虑大型实例时。