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Military missions are highly dynamic and uncertain. This characteristic comes from the nature of battlefields where such factors as enemies and terrains are not easy to be determined. Hence disruption of missions is likely to occur whenever happening a change. This requires generating plans that can adapt quickly to changes during execution of missions, while paying a less cost. In this paper, we propose a computational approach for adaptation of mission plans dealing with any possible disruption caused by changes. It 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 a computational framework, which has an evolutionary mechanism for adapting 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.