Bounded Suboptimal Weight-Constrained Shortest-Path Search via Efficient Representation of Paths
Keywords: Heuristic Search, Weight-Constrained Shortest-Path Problem, Suboptimal Search
Abstract: In the Weight-Constrained Shortest-Path (WCSP) problem, given a graph in which each edge is annotated with a cost and a weight, a start state, and a goal state, the task is to compute a minimum-cost path from the start state to the goal state with weight no larger than a specified weight limit. While most existing works have focused on solving the WCSP problem optimally, many real-world situations admit a trade-off between efficiency and a suboptimality bound for the path cost. In this paper, we propose a novel bounded suboptimal WCSP algorithm called WC-A\*pex that is built on a state-of-the-art approximate bi-objective search algorithm called A\*pex. WC-A\*pex uses an efficient, albeit approximate, representation of paths with similar costs and weights to compute a (1 + ε)-suboptimal path, for a user-specified ε. During search, WC-A\*pex avoids storing all paths explicitly and thereby reduces the search effort while still retaining its (1 + ε)-suboptimality property. On benchmark instances that model road networks, our experimental results show that WC-A*pex with ε = 0.01 (i.e., with 1% suboptimality) achieves an order-of-magnitude speed-up over WC-A\*, a state-of-the-art WCSP algorithm, and its bounded suboptimal variant.
Category: Long
Student: Graduate
Submission Number: 264
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