Solving a bi-objective unmanned aircraft system location-allocation problem

In this paper we introduce a bi-objective location-allocation problem for Unmanned Aircraft Systems (UASs) operating in a hostile environment. The objective is to find the locations to deploy UASs and assign Unmanned Aerial Vehicles to regions for surveillance. One of the objectives is to maximize search effectiveness, while the second is the minimization of the threats posed to the UASs. These two objectives are in conflict, because they are affected differently by the proximity between the UAS locations and the target regions. First, we have formulated this problem as a mixed integer nonlinear program. Next, we have developed its linearization which can be solved by a commercial optimizer for small-scale problem instances. To solve large-scale problems, we have adopted a well-known metaheuristic for multi-objective problems, namely the elitist non-dominated sorting genetic algorithm. We have also developed a hybrid approach, which has proven to be more effective than each approach alone.

Automated summary

This paper introduces a bi-objective location-allocation problem for UASs in a hostile environment, utilizing mixed integer nonlinear programming for modeling and the elitist non-dominated sorting genetic algorithm for solving large-scale problems. By linearization and hybrid approach, the effectiveness of the solutions has been improved.