Big data based intelligent decision support system for sustainable regional development

Timely intelligent decision making is increasingly important for modern society. With the availability of big data and advanced artificial intelligence in decision making, more objective and evidence-based quantitative smart decisions can be made in a timely manner. This research proposed a big data based intelligent decision support system (B-IDSS) for sustainable business development. The system can be used by both the government agencies and corporate business (e.g. farms. mining) in advanced planning, collaboration and management. This paper also addresses the performance optimization as bilevel decision-making problem with one leader and multiple followers. An extended Kuhn-Tucker approach is introduced as one of the algorithms that can be adapted in the system

Multilevel decision-making: A survey

© 2016 Elsevier Inc. All rights reserved. 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