任务计划适应性改造优化建模及方法

Modeling and Method of Adaptive Reform and Optimization for Mission Planning

针对指挥控制(C2)组织资源层-任务计划的适应性优化问题,提出了一种方案改造代价限制条件下的任务计划适应性优化(AOMPTP)问题模型及求解算法。介绍了国内外学者对任务计划适应性优化及适应性测度的研究成果,在分析方案改造代价的必要性和衡量标准的基础上,给出了方案改造代价的定义和约束条件。在方案改造代价限制条件下,建立了以使命完成时间最短为目标的问题数学模型,设计了求解该模型的多维动态列表规划(MDLS)及循环遗传(CG)算法,使指挥员能够更好地权衡方案改造优化的性能与代价,作出决策。最后通过实验分析,验证了所提方法的有效性和适用性。

In order to solve the problems of adaptive optimization for resource layer of command and control organization-mission planning, this paper proposes a model and an algorithm of adaptive optimization of mission planning under cost of changing tasks project. Aimed at the shortest mission completion time under cost of changing project constraint, the paper introduces the achievements in scientific research of scholars at home and abroad about adaptive optimization for mission planning and adaptive measures, analyzes the necessity and measurement of the cost of changing project, defines the cost of changing project, presents the constraint, and establishes a mathematical model. The paper designs a multidimensional dy- namic list scheduling and circulative genetic algorithm to solve the model. By so doing, these are advanta- geous to commanders in balancing the property with the price of changing project and making a decision. The experimental result shows that the validity and the applicability are verified for the algorithms.