Efficiently Exploring Ordering Problems through Conflict-Directed Search


  • Jingkai Chen Massachusetts Institute of Technology
  • Cheng Fang Massachusetts Institute of Technology
  • David Wang Massachusetts Institute of Technology
  • Andrew Wang Massachusetts Institute of Technology
  • Brian Williams Massachusetts Institute of Technology


In planning and scheduling, solving problems with both state and temporal constraints is hard since these constraints may be highly coupled. Judicious orderings of events enable solvers to efficiently make decisions over sequences of actions to satisfy complex hybrid specifications. The ordering problem is thus fundamental to planning. Promising recent works have explored the ordering problem as search, incorporating a special tree structure for efficiency. However, such approaches only reason over partial order specifications. Having observed that an ordering is inconsistent with respect to underlying constraints, prior works do not exploit the tree structure to efficiently generate orderings that resolve the inconsistency. In this paper, we present Conflict-directed Incremental Total Ordering (CDITO), a conflict-directed search method to incrementally and systematically generate event total orders given ordering relations and conflicts returned by sub-solvers. Due to its ability to reason over conflicts, CDITO is much more efficient than Incremental Total Ordering. We demonstrate this by benchmarking on temporal network configuration problems that involve routing network flows and allocating bandwidth resources over time.




How to Cite

Chen, J., Fang, C., Wang, D., Wang, A., & Williams, B. (2021). Efficiently Exploring Ordering Problems through Conflict-Directed Search. Proceedings of the International Conference on Automated Planning and Scheduling, 29(1), 97-105. Retrieved from https://ojs.aaai.org/index.php/ICAPS/article/view/3464