Research On Algorithm Of Task Resource Distribution Based On MDLS And GA

Because of the uncertainty, complexity and time pressure of the task planning in joint campaign, task planning in joint campaign has been indispensable to campaign command. The cores of the task planning in joint campaign are tasks and actions. The aim of the task planning in joint campaign is how to distribute the combat resources to each task efficiently. Taking every constraints of the distribution process into account, this distribution problem is actually a combinatorial optimization problem. Currently, there are two most popular algorithms used to solve this problem including MDLS algorithm and nested genetic algorithm based on group technology. In this paper, we introduces these two algorithms in details and points out there superiorities and deficiencies respectively. Based on that, we propose an improved algorithm which is a combination of the two popular algorithms. The improved algorithm successfully absorbs the superiorities of the two popular algorithms and avoids the deficiencies of the two. Been tested by numerical example, the improved algorithm get a better result with less computational expenses. This proves the advances of the improved algorithm and the point of the research of this problem.