Decision support system based on genetic algorithm and multi-criteria satisfaction analysis (MUSA) method for measuring job satisfaction
作者: Ismahene AouadniAbdelwaheb Rebai
作者单位: 1University of Sfax, MODILS, FSEG
刊名: Annals of Operations Research, 2017, Vol.256 (1), pp.3-20
来源数据库: Springer Nature Journal
DOI: 10.1007/s10479-016-2154-z
关键词: Continuous genetic algorithmDecision support systemJob satisfactionMUSA method
原始语种摘要: In this paper, we propose a Decision Support System based on the MUSA method and the continuous genetic algorithm in order to measure job satisfaction. The objective is to help organizations evaluate and measure their employees’ satisfaction. Our study is composed of two parts. Firstly, we propose to combine continuous genetic algorithm and the MUSA method in order to obtain a robust solution of good performance. The aim of the development of this algorithm is to verify its efficiency regarding the classical MUSA algorithm. Therefore, we compare the result of continuous genetic algorithm with that of the MUSA algorithm. In the second part, we present our Decision Support Systems called “GMUSA System”, it was developed in order to facilitate the applications and the use of the GMUSA tools...
全文获取路径: Springer Nature  (合作)
影响因子:1.029 (2012)

  • algorithm 算法
  • satisfaction 满意
  • MUSA 可变方向的多菱形天线
  • genetic 遗传的
  • system 
  • method 方法
  • measuring 测量
  • support 支柱
  • managerial 经理的
  • combine 联合收割机