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Tasking allocated combat aircraft to strike targets is a complicated and time-consuming process for combat planners. Currently, the process of scheduling missions is a two to four day process. To be able to respond quickly to the changing conditions of the battlefield, the military needs to compress the time that this process requires. Despite efforts to develop computer-based tools to automatically plan missions, combat planners still manually perform most of the tasking and scheduling of aircraft and targets. Unfortunately some of the tools currently available are perceived to be complicated…mehr

Produktbeschreibung
Tasking allocated combat aircraft to strike targets is a complicated and time-consuming process for combat planners. Currently, the process of scheduling missions is a two to four day process. To be able to respond quickly to the changing conditions of the battlefield, the military needs to compress the time that this process requires. Despite efforts to develop computer-based tools to automatically plan missions, combat planners still manually perform most of the tasking and scheduling of aircraft and targets. Unfortunately some of the tools currently available are perceived to be complicated and time consuming to use by the planners. They also generate schedules that often require major manual modifications. This means the combat planners often feel it is easier and faster to schedule the missions manually. With these issues in mind, this research created a prototype-scheduling tool that strikes a balance between ease of use, accurately defining and solving the problem, and generating solutions in an operationally useful amount of time. A combination of concepts from project scheduling, object-oriented programming, heuristics methodology, and genetic algorithms form the basis for the methodology developed in the research. This methodology is then demonstrated in a computer-based tool. While the focus of this research is combat planning, the object-oriented approach developed for project scheduling has applications in both the military and civilian sector. This includes a flexible method for modeling the availability of resources.
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