Abstract

In intelligent manufacturing, it is important to schedule orders from customers efficiently. Make-to-order companies may have to reject or postpone orders when the production capacity does not meet the demand. Many such real-world scheduling problems are characterised by processing times being dependent on the start time (time dependency) or on the preceding orders (sequence dependency), and typically have an earliest and latest possible start time. We introduce and analyze four algorithmic ideas for this class of time/sequence-dependent over-subscribed scheduling problems with time windows: a novel hybridization of adaptive large neighbourhood search (ALNS) and tabu search (TS), a new randomization strategy for neighbourhood operators, a partial sequence dominance heuristic, and a fast insertion strategy. Through factor analysis, we demonstrate the performance of these new algorithmic features on problem domains with varying properties. Evaluation of the resulting general purpose algorithm on three domains—an order acceptance and scheduling problem, a real-world multi-orbit agile Earth observation satellite scheduling problem, and a time-dependent orienteering problem with time windows—shows that our hybrid algorithm robustly outperforms general algorithms including a mixed integer programming method, a constraint programming method, recent state-of-the-art problem-dependent meta-heuristic methods, and a two-stage hybridization of ALNS and TS.

中文翻译：

---

与时间/顺序有关的调度：基于通用禁忌的自适应大邻域搜索算法的设计和评估

摘要

在智能制造中，重要的是有效安排客户的订单。当生产能力不能满足需求时，按订单生产的公司可能不得不拒绝或推迟订单。许多此类现实世界中的调度问题的特征在于处理时间取决于开始时间（时间相关性）或先前顺序（顺序相关性），并且通常具有最早和最晚的可能开始时间。我们针对带有时间窗口的此类与时间/序列相关的超额调度问题，介绍并分析了四种算法思想：自适应大邻域搜索（ALNS）和禁忌搜索（TS）的新型混合，一种针对邻域算子的新随机化策略，部分序列优势启发法和快速插入策略。通过因素分析，我们演示了这些新算法功能在具有不同属性的问题域上的性能。在三个领域（订单接受和调度问题，现实世界中的多轨道敏捷地球观测卫星调度问题以及带有时间窗的时间相关定向运动问题）上对所得通用算法的评估表明，我们的混合算法在性能上表现出色通用算法包括混合整数规划方法，约束规划方法，最新的与问题相关的最新元启发式方法以及ALNS和TS的两阶段混合。