Multi-Level Decision Making

Multi-Level Decision Making

EnglishPaperback / softbackPrint on demand
Zhang Guangquan
Springer, Berlin
EAN: 9783662516348
Print on demand
Delivery on Monday, 27. of January 2025
CZK 2,633
Common price CZK 2,925
Discount 10%
pc
Do you want this product today?
Oxford Bookshop Praha Korunní
not available
Librairie Francophone Praha Štěpánská
not available
Oxford Bookshop Ostrava
not available
Oxford Bookshop Olomouc
not available
Oxford Bookshop Plzeň
not available
Oxford Bookshop Brno
not available
Oxford Bookshop Hradec Králové
not available
Oxford Bookshop České Budějovice
not available
Oxford Bookshop Liberec
not available

Detailed information

This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice.

This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters.

Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.

EAN 9783662516348
ISBN 3662516349
Binding Paperback / softback
Publisher Springer, Berlin
Publication date October 22, 2016
Pages 377
Language English
Dimensions 235 x 155
Country Germany
Readership General
Authors Gao, Ya; Lu Jie; Zhang Guangquan
Illustrations XVI, 377 p. 84 illus. in color.
Edition Softcover reprint of the original 1st ed. 2015
Series Intelligent Systems Reference Library