Search Strategies for Topological Network Optimization

Authors

  • Michael D. Moffitt Google

DOI:

https://doi.org/10.1609/aaai.v36i9.21271

Keywords:

Search And Optimization (SO), Planning, Routing, And Scheduling (PRS), Constraint Satisfaction And Optimization (CSO)

Abstract

We consider an application of combinatorial search to the optimization of topologies in series-parallel networks. We propose a recursive search over the space of decomposition trees, in which partial solutions are obtained by exploring k-way partitionings of expandable nodes. We present two complementary pruning techniques that bound the value of intermediate solutions from above and below, applying monotonic operations to the contents of unresolved leaves. We also develop a means to exploit the convexity of our objective function, so as to prevent the redundant recomputation of subcircuit configurations. Finally, we evaluate our approach on a parameterized benchmark suite of electrical circuits, demonstrating over an order of magnitude improvement in performance as compared to a baseline implementation.

Downloads

Published

2022-06-28

How to Cite

Moffitt, M. D. (2022). Search Strategies for Topological Network Optimization. Proceedings of the AAAI Conference on Artificial Intelligence, 36(9), 10299-10308. https://doi.org/10.1609/aaai.v36i9.21271

Issue

Section

AAAI Technical Track on Search and Optimization