Journal of Scheduling ( IF 2 ) Pub Date : 2021-09-13 , DOI: 10.1007/s10951-021-00699-2 Florian Mischek 1 , Nysret Musliu 1 , Andrea Schaerf 2
The Test Laboratory Scheduling Problem (TLSP) is a real-world scheduling problem that extends the well-known Resource-Constrained Project Scheduling Problem (RCPSP) by several new constraints. Most importantly, the jobs have to be assembled out of several smaller tasks by the solver, before they can be scheduled. In this paper, we introduce different metaheuristic solution approaches for this problem. We propose four new neighborhoods that modify the grouping of tasks. In combination with neighborhoods for scheduling, they are used by our metaheuristics to produce high-quality solutions for both randomly generated and real-world instances. In particular, Simulated Annealing managed to find solutions that are competitive with the best known results and improve upon the state-of-the-art for larger instances. The algorithm is currently used for the daily planning of a large real-world laboratory.
中文翻译:
具有可变任务分组的测试实验室调度问题的局部搜索方法
测试实验室调度问题 (TLSP) 是一个现实世界的调度问题,它通过几个新的约束扩展了众所周知的资源约束项目调度问题 (RCPSP)。最重要的是,作业必须由求解器从几个较小的任务中组合而成,然后才能进行调度。在本文中,我们针对这个问题介绍了不同的元启发式解决方案。我们提出了四个修改任务分组的新社区。与用于调度的邻域相结合,我们的元启发式算法使用它们为随机生成的实例和现实世界的实例生成高质量的解决方案。特别是,模拟退火设法找到了与最佳已知结果相竞争的解决方案,并针对较大实例改进了最新技术。