研发型企业多项目人力资源调度研究——基于蚁群优化的超启发式算法

doi:10.3969/j.issn.1007-7375.2018.04.013

工业工程 ›› 2018, Vol. 21 ›› Issue (4): 104-109.doi: 10.3969/j.issn.1007-7375.2018.04.013

• 专题论述 • 上一篇

研发型企业多项目人力资源调度研究——基于蚁群优化的超启发式算法

伊雅丽^1,2

1. 中国科学院大学经济与管理学院, 北京 100049;
2. 中国科学院空间应用工程与技术中心, 北京 100094

收稿日期:2017-12-19 出版日期:2018-08-30 发布日期:2018-08-27
作者简介:伊雅丽(1994-),女,山西省人,硕士研究生,主要研究方向为工程项目管理.
基金资助:
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）

A Research on Multi-Project Human Resource Scheduling in R & D Enterprises——A Hyper-Heuristic Algorithm Based on Ant Colony Optimization

YI Yali^1,2

1. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100049, China;
2. Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China

Received:2017-12-19 Online:2018-08-30 Published:2018-08-27

摘要/Abstract

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。

关键词: 蚁群优化, 超启发式算法, 人力资源调度

Abstract: 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.

Key words: ant colony optimization, hyper-heuristic algorithm, human resource scheduling

中图分类号:

C931.2

伊雅丽. 研发型企业多项目人力资源调度研究——基于蚁群优化的超启发式算法[J]. 工业工程, 2018, 21(4): 104-109.

YI Yali. A Research on Multi-Project Human Resource Scheduling in R & D Enterprises——A Hyper-Heuristic Algorithm Based on Ant Colony Optimization[J]. Industrial Engineering Journal , 2018, 21(4): 104-109.

参考文献

[1] BLAZEWICZ J, LENSTRA J K, KAN A H G R. Scheduling subject to resource constraints:classification and complexity[J]. Discrete Applied Mathematics, 1983, 5(1):11-24
[2] ALVAREZ-VALDES R, TAMARIT J M. Heuristic algorithms for resource-constrained project scheduling:a review and an empirical analysis[J]. Advances in project scheduling, 1989,15(2):125-134
[3] KOLISCH R. Serial and parallel resource-constrained project scheduling methods revisited:theory and computation[J]. European Journal of Operational Research, 1996, 90(2):320-333
[4] KOLISCH R. Efficient priority rules for the resource-constrained project scheduling problem[J]. Journal of Operations Management, 1996, 14(3):179-192
[5] 张连营, 李彦伟, 孙若昕. 基于优先规则的模糊资源受限多项目调度[J]. 工业工程, 2014, 17(3):13-17 ZHANG Lianying, LI Yanwei, SUN Ruoxin. Fuzzy resource constrained multi-project scheduling based on precedence rules[J]. Industrial Engineering, 2014, 17(3):13-17
[6] WU M C, SUN S H. A project scheduling and staff assignment model considering learning effect[J]. The International Journal of Advanced Manufacturing Technology, 2006, 28(11):1190-1195
[7] 王一帆, 刘士新, 陈迪. 求解多技能人力资源约束的项目调度问题的两阶段算法[J]. 东北大学学报(自然科学版), 2014, 35(2):184-189 WANG Yifan, LIU Shixin, CHEN Di. The two stage algorithm for solving the project scheduling problem of multi-skilled human resource constraints[J]. Journal of Northeastern University(Natural Science Edition), 2014, 35(2):184-189
[8] GONÇALVES J F, MENDES J J M, RESENDE M G C. A genetic algorithm for the resource constrained multi-project scheduling problem[J]. European Journal of Operational Research, 2008, 189(3):1171-1190
[9] 王乐衡. 考虑多元设备类型的超启发式跨单元调度方法[D]. 北京:北京理工大学, 2015 WANG Leheng. Hyper-heuristic method cross unit scheduling considering multiple device types[D]. Beijing:Beijing Institute of Technology, 2015
[10] 付芳, 周泓. 多项目人力资源调度实证研究[J]. 管理工程学报, 2011, 25(3):73-77 FU Fang, ZHOU Hong. An empirical study on multi-project human resource scheduling[J]. Journal of Management Engineering, 2011, 25(3):73-77
[11] ANAGNOSTOPOULOS K P, KOULINAS G K. A genetic hyperheuristic algorithm for the resource constrained project scheduling problem[C/OL].(2010-07-18). https://ieeexplore.ieee.org/document/55864881
[12] KOULINAS G, KOTSIKAS L, ANAGNOSTOPOULOS K. A particle swarm optimization based hyper-heuristic algorithm for the classic resource constrained project scheduling problem[J]. Information Sciences, 2014, 277(2):680-693
[13] PONSTEEN A, KUSTERS R J. Classification of human- and automated resource allocation approaches in multi-project management[J]. Procedia - Social and Behavioral Sciences, 2015, 194:165-173
[14] BHASKAR T, PAL M N, PAL A K. A heuristic method for RCPSP with fuzzy activity times[J]. European Journal of Operational Research, 2011, 208(1):57-66
[15] KOLISCH R, SPRECHER A, DREXL A. Characterization and generation of a general class of resource-constrained project scheduling problems[J]. Management Science, 1995, 41(10):1693-1703

研发型企业多项目人力资源调度研究——基于蚁群优化的超启发式算法

A Research on Multi-Project Human Resource Scheduling in R & D Enterprises——A Hyper-Heuristic Algorithm Based on Ant Colony Optimization

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