[1]吴昊,杨佳,王会颖,等.求解人力资源分配问题的多目标和声搜索算法[J].计算机技术与发展,2013,(02):65-68.
 WU Hao,YANG Jia,WANG Hui-ying,et al.Multi-objective Harmony Search Algorithm for Solving Human Resource Allocation Problem[J].,2013,(02):65-68.
点击复制

求解人力资源分配问题的多目标和声搜索算法()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年02期
页码:
65-68
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Multi-objective Harmony Search Algorithm for Solving Human Resource Allocation Problem
文章编号:
1673-629X(2013)02-0065-04
作者:
吴昊12杨佳12王会颖12尹道明12
[1]合肥工业大学 管理学院;[2]教育部过程优化与智能决策重点实验室
Author(s):
WU HaoYANG JiaWANG Hui-yingYIN Dao-ming
关键词:
资源分配问题多目标优化和声搜索算法
Keywords:
resource allocation problemmulti-objective optimizationharmony search algorithm
文献标志码:
A
摘要:
人力资源分配问题是将若干个人力资源合理分配给若干个工作任务,从而达到人力生产效率最大化与人力生产成本最小化.文中提出一种改进的多目标和声搜索(MOIHS)算法来求解人力资源分配问题. MOIHS算法是通过改变记忆考虑的选择机制与微调概率来改进基本的和声算法提高算法收敛稳定性,并采用快速非支配排序方法与建立动态拥挤的距离来获得一个分布良好的Pareto解集.在求解人力资源分配问题时,同时优化人力生产成本最小化与效率最大化两个目标,最后通过一个实例可以得到在解决该问题上多目标改进和声搜索算法优于多目标遗传算法,求出的解集也具有良好的分布性
Abstract:
The human resource allocation problem seeks to find the expected objectives by allocating the limited amount of resource to va-rious activates. In this paper,a new multi-objective improved harmony search (MOIHS) has been proposed and applied to human re-source allocation problem to simultaneously optimize two goals about the cost minimization and efficiency maximization. MOIHS im-proves the base harmony search by changing the selection mechanism of memory consideration and the fine-tuning probability. It also u-ses the rapid non-dominate sorting method and establishes the dynamic crowded distance to get a good distribution of Pareto solution set. The experiment results show that,the improved harmony search is better than genetic algorithm for multi-objective resource allocation problem,it is able to give a well distributed Pareto-optimal solution

相似文献/References:

[1]廖宁 刘建勋 王俊年.DPSO算法在服务网格资源调度中的应用[J].计算机技术与发展,2009,(08):104.
 LIAO Ning,LIU Jian-xun,WANG Jun-nian.Application of Discrete Particle Swarm Optimization Algorithm to Service Grid Resource Optimization Scheduling[J].,2009,(02):104.
[2]鲍娜 张德贤 孙傲冰 王飞.基于改进蚁群算法的网格组合拍卖资源分配[J].计算机技术与发展,2009,(10):149.
 BAO Na,ZHANG De-xian,SUN Ao-bing,et al.Research on Resource Allocation of Combinatorial Auction in Grid Based on Improved Ant Colony Algorithm[J].,2009,(02):149.
[3]王丽红 倪志伟 高雅卓.改进的蚁群算法求解多目标车间作业调度问题[J].计算机技术与发展,2008,(10):49.
 WANG Li-hong,NI Zhi-wei,GAO Ya-zhuo.An Improved Ant Colony Algorithm for Multi - Objective Job - Shop Scheduling Problem[J].,2008,(02):49.
[4]饶玉佳 程家兴 夏军 李志俊.基于佳点集的多目标遗传算法[J].计算机技术与发展,2008,(12):67.
 RAO Yu-jia,CHENG jia-xing,XIA Jun,et al.Multi- Objective Optimization Genetic Algorithm Based on Good Point Set[J].,2008,(02):67.
[5]罗景峰 刘艳秋.一种全终端网络可靠性多目标优化模型及求解[J].计算机技术与发展,2007,(08):23.
 LUO Jing-feng,LIU Yan-qiu.A Multi- Objective Optimization Model for All- Terminal Networks Reliability and Its Solutions[J].,2007,(02):23.
[6]王越,吕光宏.改进的粒子群求解多目标优化算法[J].计算机技术与发展,2014,24(02):42.
 WANG Yue,Lü Guang-hong.Modified Particle Swarm Optimization Algorithm Solving Multi-objective[J].,2014,24(02):42.
[7]殷小龙,李君,万明祥. 云环境下基于改进NSGA II的虚拟机调度算法[J].计算机技术与发展,2014,24(08):71.
 YIN Xiao-long,LI Jun,WAN Ming-xiang. Virtual Machines Scheduling Algorithm Based on Improved NSGA II in Cloud Environment[J].,2014,24(02):71.
[8]刘慧慧. 一种改进的粒子群多目标优化算法研究[J].计算机技术与发展,2015,25(01):87.
 LIU Hui-hui. Research on an Improved Multi-objective Optimization Algorithm of Particle Swarm[J].,2015,25(02):87.
[9]黄志川,吴蒙. 多目标优化的相控阵三维方向调制方法[J].计算机技术与发展,2016,26(11):111.
 HUANG Zhi-chuan,WU Meng. Three-dimensional Direction Modulation of Phased Array Based on Multi-objective Optimization[J].,2016,26(02):111.
[10]娄艳秋[],庄毅[],顾晶晶[],等. 协同干扰环境下基于IMOABC的任务调度方法[J].计算机技术与发展,2017,27(11):46.
 LOU Yan-qiu[],ZHUANG Yi[],GU Jing-jing[],et al. A Task Scheduling Method Based on IMOABC in Collaboration Interference Environment[J].,2017,27(02):46.

更新日期/Last Update: 1900-01-01