TY - JOUR
T1 - Multilevel decision-making
T2 - A survey
AU - Lu, Jie
AU - Han, Jialin
AU - Hu, Yaoguang
AU - Zhang, Guangquan
N1 - Publisher Copyright:
© 2016 Elsevier Inc. All rights reserved.
PY - 2016/6/10
Y1 - 2016/6/10
N2 - Multilevel decision-making techniques aim to deal with decentralized management problems that feature interactive decision entities distributed throughout a multiple level hierarchy. Significant efforts have been devoted to understanding the fundamental concepts and developing diverse solution algorithms associated with multilevel decision-making by researchers in areas of both mathematics/computer science and business areas. Researchers have emphasized the importance of developing a range of multilevel decision-making techniques to handle a wide variety of management and optimization problems in real-world applications, and have successfully gained experience in this area. It is thus vital that a high quality, instructive review of current trends should be conducted, not only of the theoretical research results but also the practical developments in multilevel decision-making in business. This paper systematically reviews up-to-date multilevel decision-making techniques and clusters related technique developments into four main categories: bi-level decision-making (including multi-objective and multi-follower situations), tri-level decision-making, fuzzy multilevel decision-making, and the applications of these techniques in different domains. By providing state-of-the-art knowledge, this survey will directly support researchers and practical professionals in their understanding of developments in theoretical research results and applications in relation to multilevel decision-making techniques.
AB - Multilevel decision-making techniques aim to deal with decentralized management problems that feature interactive decision entities distributed throughout a multiple level hierarchy. Significant efforts have been devoted to understanding the fundamental concepts and developing diverse solution algorithms associated with multilevel decision-making by researchers in areas of both mathematics/computer science and business areas. Researchers have emphasized the importance of developing a range of multilevel decision-making techniques to handle a wide variety of management and optimization problems in real-world applications, and have successfully gained experience in this area. It is thus vital that a high quality, instructive review of current trends should be conducted, not only of the theoretical research results but also the practical developments in multilevel decision-making in business. This paper systematically reviews up-to-date multilevel decision-making techniques and clusters related technique developments into four main categories: bi-level decision-making (including multi-objective and multi-follower situations), tri-level decision-making, fuzzy multilevel decision-making, and the applications of these techniques in different domains. By providing state-of-the-art knowledge, this survey will directly support researchers and practical professionals in their understanding of developments in theoretical research results and applications in relation to multilevel decision-making techniques.
KW - Bi-level programming
KW - Fuzzy decision-making
KW - Multilevel decision-making
UR - http://www.scopus.com/inward/record.url?scp=84959364410&partnerID=8YFLogxK
U2 - 10.1016/j.ins.2016.01.084
DO - 10.1016/j.ins.2016.01.084
M3 - Article
AN - SCOPUS:84959364410
SN - 0020-0255
VL - 346-347
SP - 463
EP - 487
JO - Information Sciences
JF - Information Sciences
ER -