摘要
现阶段,研发型企业的项目处于多项目环境下,为了解决多项目并行时人力资源争夺问题,本文针对该类企业多项目管理中人力资源调度进行优化研究,以考虑项目延期惩罚成本的最小总成本为目标函数,将现实问题抽象建模。基于国内外的研究提出了一种超启发式算法进行求解,该算法将人力资源调度问题分为项目活动分配和人员选择项目活动两个部分,采用蚁群优化作为高层启发式策略搜索低层启发式规则,再进一步根据规则解构造出可行解。最后本研究设计多组仿真实验与启发式规则进行对比,结果表明该算法有较好的搜索性能,为人力资源的调度问题提供了新的解决方案。
At present,the project of R&D enterprises is in multi-project environment.In order to solve the human resource contention in multi-project management,this kind of enterprise is studied for optimizing the human resource scheduling in the multi-project management.The minimum total cost is taken as the objective function by taking the delay penalty cost into consideration,and the real problem is modelled.An algorithm which is“hyper-heuristic”based on ant colony optimization is used to solve the problem.The algorithm divides the problem into two parts,project activity allocation and selection,and it uses ant colony optimization as high-level heuristic strategy to search low level heuristic rules,then generates feasible solutions according to the rules.Multiple sets of simulation experiments are designed to compare this algorithm with the combination of heuristic rules.the experimental results show that the algorithm performs a better search performance overall,and it provides a new solution to the scheduling problem for human resources.
作者
伊雅丽
YI Yali(School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100049,China;Technology and Engineering Center for Space Utilization,Chinese Academy of Sciences,Beijing 100094,China)
出处
《工业工程》
北大核心
2018年第4期104-109,共6页
Industrial Engineering Journal
基金
中国科学院青年创新促进专项基金资助项目(CASYI2014135)
中国科学院太空应用创新基金资助项目(CXJJ-16S064)
关键词
蚁群优化
超启发式算法
人力资源调度
ant colony optimization
hyper-heuristic algorithm
human resource scheduling
