摘要
按照资源效率最大化原则,由层次分析法求出基于多项目比较的进度贡献权向量,引入融合模拟退火思想的改进粒子群算法,动态解决各时点不同利益主体之间瓶颈资源冲突。依次构建了以资源调配额为决策变量的两个优化子模型:一是令资源使用计划向前推进,充分发挥现有生产能力加快施工进程;二是在项目群工期受控的可行域内,迭代得到业主净现值的帕累托改进解。通过编写Matlab代码,开展Z项目群案例分析。结果表明:研究模型显著提高了生产负荷率,极大程度地改善了砂石料系统运维的稳定性,有效地化解合同项目时序约束与资源多任务之间的矛盾,从而逐步达到了项目群工期—费用的集成与协调。
According to the principle of efficiency maximization,this paper uses the analytic hierarchy process to obtain the progress contribution weight vector based on the comparison of multiple projects,and introduces the improved particle swarm algorithm integrating the simulated annealing idea to dynamically solve the bottleneck resource conflicts between subjects at various points in time.It constructs two optimization sub-models with resource allocation quotas as decision variables.The results show that this research increases the production load rate,improves the stability of the sand and gravel system operation and maintenance,and resolves the contradiction between the time sequence constraints of the contracted project and the multi-tasking of resources.Thereby it helps to gradually facilitate the integration and coordination of the program construction duration-cost,and provides a new idea for managers to arrange large-scale projects scheduling plan.
作者
丰景春
黎书彤
陈润东
冯海瑜
FENG Jing-chun;LI Shu-tong;CHEN Run-dong;FENG Hai-yu(Hohai University,Business School,Nanjing Jiangsu,211100;Hohai University,Institute of Project Management,Nanjing Jiangsu,211100;Hohai University,International River Research Centre,Nanjing Jiangsu,211100;Jiangsu Provincial Collaborative Innovation Center of World Water Valley and Water Ecological Ciuilization,Nanjing,211100;Department of Water Resources of Guangxi Zhuang Autonomous Reggion,Nanning 530023;Guangxi Zhuang Autonomous Region Water Conservancy Project Construction Management Center,Nanning 530023)
出处
《软科学》
CSSCI
北大核心
2021年第4期112-120,共9页
Soft Science
基金
国家社会科学基金项目(17BGL156)
住房和城乡建设部2018年科学技术项目(2018-K8-23)。
关键词
项目群
甲供非商品化资源
两阶段工期—费用优化
混合粒子群算法
层次分析法
programs
non-commercial resource provided by employer
two-stage duration-cost optimization
hybrid particle swarm algorithm
analytic hierarchy process
