摘要
以最大化覆盖收益和最小化覆盖代价为优化目标,建立了多浮空器区域覆盖布局优化问题的多目标混合整数规划模型,设计实现了多浮空器联合覆盖进化算法,充分利用目标位置、浮空器覆盖能力等启发式信息构造初始种群,避免进化太慢;交叉、变异算子在保证有效解的前提下,避免了算法陷入局部最优;精英策略避免丢失进化过程产生的非劣解,加快算法收敛;外部种群用于存储迭代过程中得到的非劣解,并保证解的多样性。仿真实验表明,算法能够有效解决浮空器区域覆盖布局优化同题。
A multi-objective mixed integer programming model for the Multi-Airship Area Covering Deployment Optimization Problem（MAACDOP） is presented.MAACDOP takes the available quantity of airship and their coverage capability into account.The objectives are to maximize the coverage profits and minimize the total construction cost.Then a Multi-Airship Cooperative Covering Evolutionary Algorithm （MACCEA） is proposed.Taking full advantage of the heuristic information related to the target position and the airship coverage capability,MACCEA can construct the initial solutions and avoid converging slowly in the process of evolution.Problem specific crossover and mutation operators ensure the feasibility of the children so as to prevent the algorithm from falling into local optimum.Elitism mechanism is adopted to prevent losing non-dominated individuals generated during the evolutionary process and speed up the convergence of the algorithm.Use an external archive to store the non-dominated solutions in the iterations,and guarantee the diversity of the solutions.The simulation results testified that the algorithm can solve the MAACDOP effectively.
出处
《火力与指挥控制》
CSCD
北大核心
2011年第11期137-140,共4页
Fire Control & Command Control
关键词
浮空器
布局优化
进化算法
多目标优化
airship
deployment optimization
evolutionary algorithm
MOP
