An evolutionary multi-objective approach for dynamic mission planning

In this paper, we propose a computational approach for adaptation in mission planning, an important process in the chain of command and control. In this area, it has been highly regarded that military missions are often dynamic and uncertain. This characteristic comes from the nature of battlefields where the factors of enemies and terrains are not easy to be determined. Hence, it is necessary to generate plans that can adapt quickly to the changes during the missions, while avoiding paying a high cost. In addressing such an adaptation process, the issue of multi-objectivity can not be avoided. Our approach first mathematically models the dynamic planning problem with two criteria: the mission execution time and the cost of operations. Based on this quantification, we introduce an evolutionary multi-objective mechanism to adapt the current solution to new situations resulted from changes. We carried out a case study on this newly proposed approach. A modified military scenario of a mission was used for testing. The obtained results strongly support our proposal in finding adaptive solution dealing with the changes.