用惰性子句生成法求解具有广义优先级的资源受限项目调度问题
Solving the Resource Constrained Project Scheduling Problem with Generalized Precedences by Lazy Clause Generation
摘要：
该技术报告提出了一种通用的精确解方法，用于最小化具有广义优先级（Rcpsp/max）的资源受限项目调度问题的项目工期。该方法使用惰性子句生成，即，一个有限域和布尔可满足性求解的混合体，以应用nogood学习和冲突驱动搜索的解决方案生成。我们的实验表明，懒惰条款生成的好处，找到一个最佳的解决方案，并证明其最优性相比，其他国家的最先进的精确和非精确的方法。该方法具有高度耐用性：根据PSPLib上当前可用的数据，它匹配或优于我们检查的所有2340个实例中最知名的结果，除了3个。在这个集合中的631个开放实例中，它关闭了573个，并改进了其余58个实例中的51个的边界。
英文摘要：
The technical report presents a generic exact solution approach for minimizing the project duration of the resource-constrained project scheduling problem with generalized precedences (Rcpsp/max). The approach uses lazy clause generation, i.e., a hybrid of finite domain and Boolean satisfiability solving, in order to apply nogood learning and conflict-driven search on the solution generation. Our experiments show the benefit of lazy clause generation for finding an optimal solutions and proving its optimality in comparison to other state-of-the-art exact and non-exact methods. The method is highly robust: it matched or bettered the best known results on all of the 2340 instances we examined except 3, according to the currently available data on the PSPLib. Of the 631 open instances in this set it closed 573 and improved the bounds of 51 of the remaining 58 instances.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
