Team formation based on group technology: A hybrid grouping genetic algorithm approach

被引：40

作者：

Agustin-Blas, Luis E. ^{[1
]}

Salcedo-Sanz, Sancho ^{[1
]}

Ortiz-Garcia, Emilio G. ^{[1
]}

Portilla-Figueras, Antonio ^{[1
]}

Perez-Bellido, Angel M. ^{[1
]}

Jimenez-Fernandez, Silvia ^{[1
]}

机构：

[1] Univ Alcala de Henares, Grp Heurist Modernos Optimizac & Diseno Rede GHEO, Dept Signal Theory & Commun, Madrid 28871, Spain

来源：

COMPUTERS & OPERATIONS RESEARCH | 2011年 / 38卷 / 02期

关键词：

Team formation; Group technology; Grouping genetic algorithms; Hybrid algorithms; CELL-FORMATION; EFFICIENCY MEASURES; DECISION-SUPPORT; EFFICACY; MATRICES; SYSTEM;

D O I：

10.1016/j.cor.2010.07.006

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents a new model for team formation based on group technology (TFPGT). Specifically, the model is applied as a generalization of the well-known Machine-Part Cell Formation problem, which has become a classical problem in manufacturing in the last few years. In this case, the model presented is especially well-suited for problems of team formation arising in R&D-oriented or teaching institutions. A parallel hybrid grouping genetic algorithm (HGGA) is also proposed in the paper to solve the TFPGT. The performance of the algorithm is shown in several synthetic TFPGT instances, and in a real problem: the formation of teaching groups at the Department of Signal Theory and Communications of the Universidad de Alcala in Spain. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：484 / 495

页数：12

共 34 条

[1] A hybrid grouping genetic algorithm for assigning students to preferred laboratory groups [J].