基于改进NSGA-II的多项目多技能人力资源调度研究

doi:10.3969/j.issn.1007-7375.2021.03.017

工业工程 ›› 2021, Vol. 24 ›› Issue (3): 130-138.doi: 10.3969/j.issn.1007-7375.2021.03.017

基于改进NSGA-II的多项目多技能人力资源调度研究

王莹莹, 吴立云

河南理工大学能源科学与工程学院，河南焦作 454000

收稿日期:2020-02-23 发布日期:2021-06-26
通讯作者: 吴立云(1973-),女,河北省人,副教授,博士,主要研究方向为安全系统工程、现代物流与供应链管理。E-mail:jitwly@hpu.edu.cn E-mail:jitwly@hpu.edu.cn
作者简介:王莹莹(1993-)，女，河南省人，硕士研究生，主要研究方向为项目调度、人力资源
基金资助:
国家自然科学基金项目资助（51674102，51874121）；河南省重点科技攻关计划资助项目（182102310002）；河南省高校基本科研业务费专项资金资助（NSFRF180104）；NSFC-河南联合基金重点资助项目（U1904210）

A Research on Multi-project Multi-skill Human Resource Scheduling Based on Improved NSGA-II

WANG Yingying, WU Liyun

School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454000, China

Received:2020-02-23 Published:2021-06-26

摘要/Abstract

摘要： 多项目并行的人力资源管理日益成为研发型企业合理配置各类资源、实现利润最大化的有效方式。从项目成本和多能工满意度角度出发，运用第2代非支配排序遗传算法和蚁群算法对多能工分配问题进行研究。考虑多能工技能组合与项目任务需求之间的匹配以及技能熟练水平对任务作业时间的影响，构建了以实现多项目总工期和多能工间工作量均衡为目标的优化模型。根据模型的约束条件，提出了一系列启发式规则提高算法效率，并结合第2代非支配排序遗传算法和蚁群算法的特点，利用新开发的算法对模型进行求解。通过数值算例验证了模型和算法的有效性。

关键词: 项目调度, 非支配排序遗传算法, 人力资源, 多项目, 多技能

Abstract: When multiple projects work at the same time, rational allocation of various resources and pursuit of greater economic profits through human resource management have become the focus of research and development enterprises. From the perspective of project cost and satisfaction of multi-skilled workers, the second-generation non-dominated sorting genetic algorithm and ant colony algorithm are used to study the allocation of multi-skilled workers. Considering the matching between the skill mix of multi-skilled workers and the needs of project tasks and the impact of skill proficiency on task operation time, an optimization model is constructed that aims to achieve the total duration of multi-projects and the workload balance among multi-skilled workers. According to the constraints of the model, a series of heuristic rules are proposed to improve the efficiency of the algorithm. The algorithm is developed by combining the characteristics of the second-generation non-dominated sorting genetic algorithm and ant colony algorithm to solve the model. Numerical examples verify the effectiveness of the model and algorithm.

Key words: project scheduling, non-dominated sorting genetic algorithm, human resources, multi-project, multi-skill

中图分类号:

F224.5

王莹莹, 吴立云. 基于改进NSGA-II的多项目多技能人力资源调度研究[J]. 工业工程, 2021, 24(3): 130-138.

WANG Yingying, WU Liyun. A Research on Multi-project Multi-skill Human Resource Scheduling Based on Improved NSGA-II[J]. Industrial Engineering Journal, 2021, 24(3): 130-138.

参考文献

[1] WU M C, SUN S H. A project scheduling and staff assignment model considering learning effect[J]. International Journal of Advanced Manufacturing Technology, 2006, 28(11): 1190-1195
[2] 付芳, 周泓. 基于免疫遗传算法和列生成的多项目人力资源调度研究[J]. 中国管理科学, 2010, 18(2): 120-126
FU Fang, ZHOU Hong. Multi-project scheduling problem with human resources based on genetic algorithm and column generation[J]. Chinese Journal of Management Science, 2010, 18(2): 120-126
[3] 肖菁, 吴洲. 基于时间轴的软件多项目任务调度遗传算法[J]. 计算机科学, 2012, 39(12): 133-138
XIAO Jing, WU Zhou. Software multi-project scheduling genetic algorithms based on a time-line model[J]. Computer Science, 2012, 39(12): 133-138
[4] HEIEMERL C, KOLISCH R. Scheduling and staffing multiple projects with a multi-skilled workforce[J]. Operation Research Spectrum, 2010, 32(2): 343-368
[5] MYSZKOWSKI P B, SKOWRONSKI M E, OLECH Ł P, et al. Hybrid ant colony optimization in solving multi-skill resource-constrained project scheduling problem[J]. Soft Computing, 2015, 19: 3599-3619
[6] YANNIBELLI V, AMANDI A. Hybridizing a multi-objective simulated annealing algorithm with a multi-objective evolutionary algorithm to solve a multi-objective project scheduling problem[J]. Expert Systems with Applications, 2013, 40(7): 2421-2434
[7] BARZ C, KOLISCH R. Hierarchical multi-skill resource assignment in the telecommunications industry[J]. Production and Operations Management, 2014, 23(3): 489-503
[8] 陈蓉, 梁昌勇, 叶春森, 等. 考虑随机离职的新产品研发项目组合多技能员工调度模型[J]. 系统工程理论与实践, 2018, 38(1): 164-176
CHEN Rong, LIANG Changyong, YE Chunsen, et al. A multi-skilled staff scheduling model for new product R & D project portfolio under stochastic turnover[J]. Systems Engineering—Theory & Practice, 2018, 38(1): 164-176
[9] 刘振元, 袁慧涛, 周成, 等. 多技能资源时间窗约束下可中断项目调度的分支定界算法[J]. 系统工程理论与实践, 2019, 39(1): 183-199
LIU Zhengyuan, YUAN Huitao, ZHOU Cheng, et al. Branch-and-bound based approach for preemptive project scheduling with time-window constraints on multi-skilled resources[J]. Systems Engineering—Theory & Practice, 2019, 39(1): 183-199
[10] HANNE T, NICKEL S. A multi-objective evolutionary algorithm for scheduling and inspection planning in software development projects[J]. European Journal of Operational Research, 2005, 167(3): 663-678
[11] CHEN J, WANG S. JIANG J P. Method research for dynamic multi-project human resource allocation based on multidimensional model[C]. 2011 2nd International Conference on Management Science and Engineering (MSE 2011). Chengdu: 2011.
[12] 陈俊杰, 同淑荣, 聂亚菲, 等. 考虑胜任力水平的研发项目群人力资源调度[J]. 计算机工程与应用, 2019, 55(3): 214-223
CHEN Junjie, TONG Shurong, NIE Yafei, et al. R& D program scheduling and staff assignment with hierarchical levels of competency[J]. Computer Engineering and Applications, 2019, 55(3): 214-223
[13] 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
[14] 廉洁, 刘晨光, 殷勇. Seru生产方式下考虑工人异质性的多能工分配模型及算法[J]. 运筹与管理, 2019, 28(2): 85-93
LIAN Jie, LIU Chenguang, YIN Yong. Mathematical model and algorithm for multi-skilled worker assignment problem in seru production systems considering the worker heterogeneity[J]. Operations Research & Management Science, 2019, 28(2): 85-93
[15] 廖婷婷, 徐哲, 李明. 软件开发项目多技能人力资源均衡调度模型[J]. 工业工程, 2015, 18(3): 72-77
LIAO Tingting, XU Zhe, LI Ming. A research on multi-skill human resource leveling scheduling model of software development project[J]. Industrial Engineering Journal, 2015, 18(3): 72-77
[16] VILA GONCALVES FILHO E, TIBERTI A J. A group genetic algorithm for the machine cell formation problem[J]. International Journal of Production Economics, 2006, 102(1): 1-21
[17] DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197
[18] FALKENAUER E. Genetic algorithms for grouping problems[M]. New York: Wiley, 1998.
[19] ZITZLER E, THIELE L. Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach[J]. IEEE Transactions on Evolutionary Computation, 1999, 3(4): 257-271

基于改进NSGA-II的多项目多技能人力资源调度研究

A Research on Multi-project Multi-skill Human Resource Scheduling Based on Improved NSGA-II

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 11

编辑推荐

Metrics

本文评价

[1]	杜宏飞, 王小明, 陈庆新, 毛宁. 考虑公有与私有资源约束的多项目调度规则对比研究[J]. 工业工程, 2021, 24(5): 141-151.
[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.
[3]	杨斌彬, 叶春明. 现场维修服务的多服务中心的多技能工调度研究[J]. 工业工程, 2017, 20(5): 58-65.
[4]	郝志刚. 考虑医患满意度和手术成本的日手术排程方法[J]. 工业工程, 2017, 20(4): 49-56,71.
[5]	何立华，马芳丽. 基于混沌差分进化粒子群算法的模糊资源受限项目调度问题[J]. 工业工程, 2016, 19(5): 39-44.
[6]	李明1,2, 徐哲2. 基于均衡优化的项目多技能人力资源指派与调度方法[J]. 工业工程, 2016, 19(1): 108-114.
[7]	廖婷婷，徐哲，李明. 软件开发项目多技能人力资源均衡调度模型[J]. 工业工程, 2015, 18(3): 69-74.
[8]	张连营1, 李彦伟1,2, 孙若昕1. 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.
[9]	郭云涛，宋红艳，白思俊. 粒子群算法在具有迭代关系资源受限项目调度中的应用[J]. 工业工程, 2013, 16(5): 74-78.
[10]	梁祖红，陈庆新，毛宁. 考虑合同期的多类人员协同工作人力资源计划[J]. 工业工程, 2012, 15(4): 78-82.
[11]	谢阳，叶春明，陈君兰，周蓉. 基于混沌粒子群的资源受限项目调度问题[J]. 工业工程, 2012, 15(3): 57-61.