Efficient Algorithms for Boundary Defense with Heterogeneous Defenders

TL;DR

This paper introduces efficient algorithms for boundary defense involving heterogeneous defenders, optimizing attack interception with network flow and integer programming methods, validated through extensive simulations.

Contribution

It presents novel network-flow and integer programming algorithms for boundary defense, reducing computational complexity and enabling analysis of various defense scenarios.

Findings

Algorithms significantly outperform previous methods in computation time.

Defense effectiveness varies with defender heterogeneity and attack parameters.

Solution structures reveal key relationships between parameters and interception success.

Abstract

This paper studies the problem of defending (1D and 2D) boundaries against a large number of continuous attacks with a heterogeneous group of defenders. The defender team has perfect information of the attack events within some time (finite or infinite) horizon, with the goal of intercepting as many attacks as possible. An attack is considered successfully intercepted if a defender is present at the boundary location when and where the attack happens. Through proposing a network-flow and integer programming-based method for computing optimal solutions, and an exhaustive defender pairing heuristic method for computing near-optimal solutions, we are able to significantly reduce the computation burden in solving the problem in comparison to the previous state of the art. Extensive simulation experiments confirm the effectiveness of the algorithms. Leveraging our efficient methods, we also characterize the solution structures, revealing the relationships between the attack interception rate and the various problem parameters, e.g., the heterogeneity of the defenders, attack rate, boundary topology, and the look-ahead horizon.