Efficiently Exploring Ordering Problems through Conflict-directed Search

TL;DR

This paper introduces CDITO, a conflict-directed search method that efficiently generates total orderings in planning problems by reasoning over conflicts, outperforming previous partial-order approaches.

Contribution

The paper proposes a novel conflict-directed incremental total ordering algorithm that systematically resolves inconsistencies, improving efficiency in ordering problems within planning and scheduling.

Findings

CDITO outperforms previous methods in benchmark tests.

It efficiently resolves conflicts to generate consistent total orders.

Applicable to complex temporal network configuration problems.

Abstract

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.