Optimization research of enterprise project portfolio selection with considering multi-skilled workforce

Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (23): 244-248.

Optimization research of enterprise project portfolio selection with considering multi-skilled workforce

WANG Yongsheng1，2, JIANG Liying3, LENG Yajun2

1.School of Civil and Architecture, Northeast Dianli University, Jilin, Jilin 132012, China
2.School of Management, Hefei University of Technology, Hefei 230009, China
3.Organic Composed Factory of Jilin Petroleum Co., Jilin, Jilin 132022, China

Online:2012-08-11 Published:2012-08-21

考虑多技能人的企业项目组合选择优化研究

王勇胜1，2，姜利赢3，冷亚军2

1.东北电力大学建筑工程学院，吉林省吉林市 132012
2.合肥工业大学管理学院，合肥 230009
3.中国石油吉林石化有机合成厂，吉林省吉林市 132022

Abstract

Abstract: Based on the research background that there is multi-skilled workforce in enterprise skilled personnel, a hierarchical optimization model of two-stage fuzzy project portfolio selection is established. Optimization objective is maximization of the value of projects, which are selected within fuzzy scenario, and decision variable is numbers of multi-skilled workforce that is assigned into difference skilled personnel. A 0-1 integral optimization model is constructed. Because skilled personnel work in different project, their skill increases. A integral optimization model is set up, the objective function is maximization of the sum of skill increment, and decision variable is numbers of different kinds of skilled personnel that are distributed to each of the selected projects. Genetic Algorithm（GA） is adopted to solve the model, and it is effectively. Simulation test shows the hierarchical optimization model of two-stage fuzzy project portfolio selection can maximize enterprise benefits, and maximize skill increment, through assigning skilled personnel reasonably. This thesis provides a valid approach for combining of short-term and long-tem benefits of enterprise.

Key words: multi-skilled workforce, skilled increment, fuzzy, two-stage, project portfolio selection

摘要： 基于企业技能人员中存在多技能人的研究背景，建立了具有递阶结构的两阶段项目组合选择优化模型。以所选项目的模糊项目价值最大为优化目标，以多技能人在各技能上的人数分配为决策变量，构建了模糊0-1整数优化模型，采用可能性理论对其进行了确定性转换；根据技能人员在项目中工作锻炼，会形成技能增值的特点，建立了以总技能增值最大为优化目标，技能人员在所选项目中的人数分配为决策变量的整数规划模型。通过设计相应的遗传算法（GA）对模型进行了有效求解。仿真测试显示，所建递阶结构两阶段项目组合选择优化模型，可以在实现企业利益最大化前提下，通过合理的人员调配使人力技能增值达到最大，为企业实现短期和长期利益的有机结合，提供了有效的解决途径。

关键词: 多技能人, 技能增值, 模糊, 两阶段, 项目组合选择

WANG Yongsheng1，2, JIANG Liying3, LENG Yajun2. Optimization research of enterprise project portfolio selection with considering multi-skilled workforce[J]. Computer Engineering and Applications, 2012, 48(23): 244-248.

王勇胜1，2，姜利赢3，冷亚军2. 考虑多技能人的企业项目组合选择优化研究[J]. 计算机工程与应用, 2012, 48(23): 244-248.

[1]	LAN Hong, HUANG Min. Fusion of KNN Optimized Density Peaks and FCM Clustering Algorithm [J]. Computer Engineering and Applications, 2021, 57(9): 81-88.
[2]	WANG Di, LI Caihong, GUO Na, LIU Guoming, GAO Tengteng. Local Path Planning of Mobile Robot Based on Fuzzy Potential Field Method [J]. Computer Engineering and Applications, 2021, 57(6): 212-218.
[3]	DAI Qi, LI Min, LIU Yang, LI Lihong. Fast Attribute Reduction Algorithm Based on Fuzzy Hierarchical Quotient Space [J]. Computer Engineering and Applications, 2021, 57(4): 55-60.
[4]	LIU Jingsheng, WU Xing, WANG Honggang, LI Jiangnan. Improved FCOS Two-Stage SAR Ship Detection Algorithm [J]. Computer Engineering and Applications, 2021, 57(24): 144-151.
[5]	SU Fei, WANG Hong, ZU Linlu, WANG Jiang, LIU Chen. Closed-Loop Modulation of Parkinson’s State Based on Fuzzy Control [J]. Computer Engineering and Applications, 2021, 57(22): 273-280.
[6]	ZHANG Min, PENG Hongwei, YAN Xiaoling. Improved Algorithm of Fuzzy Decision Tree Based on Neural Network [J]. Computer Engineering and Applications, 2021, 57(21): 174-179.
[7]	HUI Hui, WANG Qiuping, LI Miaomiao. Hesitant Fuzzy Linguistic Regret Theory and ELECTRE Decision Making Method and Its Application [J]. Computer Engineering and Applications, 2021, 57(20): 172-179.
[8]	GAN Xinyan, GAO Xiang. Research on Cloud Manufacturing System Selection Based on Hesitant Fuzzy Decision Making Algorithm [J]. Computer Engineering and Applications, 2021, 57(2): 134-142.
[9]	QIN Boyu, HAO Xiaoyan, LIU Yongfang. Frame Disambiguation of FrameNet Based on SVM and CRF Two-Stage Model [J]. Computer Engineering and Applications, 2021, 57(18): 255-262.
[10]	BAO Shun, ZHOU Ligang. Multiple Attribute Decision Making Method Based on Additive Consistent Pythagorean Fuzzy Preference Relations [J]. Computer Engineering and Applications, 2021, 57(17): 61-67.
[11]	HUANG Lin, YUAN Xiujiu. General Formula and Generating Algorithm of Improved Hesitant Fuzzy Linguistic Entropy [J]. Computer Engineering and Applications, 2021, 57(16): 97-107.
[12]	TONG Wenlin, CHEN Dewang, HUANG Yunhu, LYU Yisheng. Fuzzy System Optimization Method Based on Simulated Annealing and Rule Reduction [J]. Computer Engineering and Applications, 2021, 57(16): 142-150.
[13]	ZHANG Junfang, ZHOU Ligang, ZHANG Chunfang, XU Xin, XIAO Jian. Application of Interval-Valued Pythagorean Hesitant Fuzzy Continuous Entropy-Grey Relative Degree [J]. Computer Engineering and Applications, 2021, 57(15): 207-214.
[14]	XIE Xiang, ZHANG Qianru, ZHANG Jing, GAO Xinyu. Research and Application on Information System Component Identification Method Based on Domain Modeling-Oriented [J]. Computer Engineering and Applications, 2021, 57(12): 105-114.
[15]	CHEN Xuejuan. Hesitant Fuzzy Group Consensus Reaching Algorithm and Its Application to Select Data System [J]. Computer Engineering and Applications, 2021, 57(11): 128-134.