Abstract: |
This paper describes an approach to air campaign mission planning using evolutionary multi-objective optimization. With the landscape of warfare constantly changing, timely and accurate employment of air assets for military operations has become even more crucial. Of particular importance is in addressing time-sensitive and time-critical targets. Such operations require a rapid search of potential mission plans to evaluate their ability on an array of objectives. This type of system design problem, consisting of a large solution space and complicated fitness landscape, has proved to be approached successfully using evolutionary algorithms. Additionally, the presence of potentially multiple conflicting objectives lends to the suitability of using multi-objective optimization techniques. This paper describes our preliminary experiments using both aggregation and dominance-based approaches to evolutionary multi-objective optimization for addressing time-sensitive/critical targets. |
