Utilizing a combination of heuristic and stochastic techniques, this work approximates solutions for complex variants of the Traveling Salesman Problem. Within this study, we seek to develop a Pareto front of time optimal solutions for a large scale, multi-objective, multi-agent, multi-depot, traveling salesman problem with turning constraints that emulates a UAV operator monitoring a swarm of autonomous vehicles. This research is a culmination of years of investigation and past publications [1, 2, 3] which sought to solve portions of this problem individually. Solving the entire problem, more precisely named the Multi-Objective Min-Max Multi-Depot Polygon Visiting Dubins Multiple Traveling Salesman Problem, follows similar processes of simpler variants. With a focus on military applications, run-time is very critical to the success of this software. Through the cooperation of these algorithms, accurate solutions for large scale problems can be produced within a quick timeframe.
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Infotech@Aerospace.