不确定型网络计划工期费用模拟优化  

Uncertainty network planning period cost of simulation and optimization

作　　者：李倩[1] 方木云[1] 吴元[1] 

机构地区：[1]安徽工业大学安徽省计算与通信软件重点实验室,安徽马鞍山243002

出　　处：《商丘师范学院学报》2011年第6期49-53,共5页Journal of Shangqiu Normal University

基　　金：国家自然科学基金资助项目(60473142)

摘　　要：针对大型项目网络计划的不确定性,研究了工期、资源不确定的网络计划在费用限制情况下的费用均衡优化问题.利用蒙特卡罗分布,对不确定型网络计划进行蒙特卡罗仿真,进而获得n次仿真结果的代表性样本,从而得到该样本对应的确定性网络,用遗传算法进行求解.克服了传统启发式资源均衡优化算法在大型网络计划中不能保证最优解的缺点,得到一个费用分布均衡的网络计划.且以实例验证了该算法对大型项目的工期资源优化具有实际的应用价值.Network planning for large projects the uncertainty of the schedule,resources,network planning in the uncertain cost of the fees under limited circumstances balanced optimization problems.Monte Carlo distribution,the network plans uncertain Monte Carlo simulation,then n times to obtain a representative sample of simulation results to obtain the certainty of the sample corresponds to the network,using the genetic algorithm.To overcome the traditional heuristic algorithm for resource leveling program in a large network can not guarantee the shortcomings of the optimal solution,get a balance of cost of the network plan.And examples show that the algorithm for large projects with a duration of resource optimization practical value.

关 键 词：不确定性 网络计划 资源均衡优化 遗传算法 

分 类 号：O225[理学—运筹学与控制论]