Decision support and control for large-scale complex systems

Abstract The technical and social systems of the present day are ever more complex and complicated objects. Their models are characterized by large numbers of state and control variables, time delays, and different time constants. Also they show constraints in their information infrastructure and risk sensitivity aspects. Such systems are called large –scale complex systems (LSS). Hierarchical approach has been for several decades one of the most utilized methodologies for controlling large-scale systems. When human intervention is necessary decision support systems (DSS) can represent a solution. A DSS is an adaptive and evolving information system meant to implement several of the functions of a human support team that would otherwise be needed to help the decision-maker to overcome his/her limits and constraints he/she may face when approaching decision problems that count in the organization. This paper aims at reviewing several aspects concerning LSS control and the utilization and technology of DSS. Particular emphasis is put on real-time DSS and multiparticipant (group) DSS. Several advanced solutions such as mixed knowledge systems, that combine numerical methods with AI-based tools, and the prospects of using Ambient Intelligence concepts in DSS construction are described.

[1]  Derek L. Nazareth,et al.  Supporting complex real-time decision making through machine learning , 1993, Decis. Support Syst..

[2]  Piotr Tatjewski,et al.  Iterative Algorithms For Multilayer Optimizing Control , 2005 .

[3]  Ralph H. Sprague,et al.  Invited Article: A Framework for the Development of Decisoin Support Systems , 1980, MIS Q..

[4]  E. B. James,et al.  The User Interface , 1980, Comput. J..

[5]  Vasant Dhar,et al.  Intelligent Decision Support Methods: The Science of Knowledge Work , 1996 .

[6]  Andrew B. Whinston,et al.  Decision Support Systems: A Knowledge Based Approach : , 1996 .

[7]  Ehl Emile Aarts Technological issues in ambient intelligence , 2003 .

[8]  Sujeet Chand FROM ELECTRIC MOTORS TO FLEXIBLE MANUFACTURING: CONTROL TECHNOLOGY DRIVES INDUSTRIAL AUTOMATION , 2005 .

[9]  Hamideh Afsarmanesh,et al.  Establishing the Foundation of Collaborative Networks , 2007 .

[10]  Herbert A. Simon,et al.  The new science of management decision , 1960 .

[11]  J. Hatvany,et al.  Intelligence and cooperation in heterarchic manufacturing systems , 1985 .

[12]  Hamideh Afsarmanesh,et al.  Balanced Automation Systems. Architectures and design methods , 1995 .

[13]  Hartmut Raffler AMBIENT INTELLIGENCE: AN INDUSTRIAL VIEW , 2007 .

[14]  J. C. R. Licklider,et al.  Man-Computer Symbiosis , 1960 .

[15]  Gunnar Johannsen Integrated Systems Engineering: The Challenging Cross-Discipline , 1995 .

[16]  Patrick Brézillon,et al.  Lecture Notes in Artificial Intelligence , 1999 .

[17]  Shimon Y. Nof Collaborative control theory for e-Work, e-Production, and e-Service , 2007, Annu. Rev. Control..

[18]  Ulrich Briefs,et al.  Re-thinking industrial work: Computer effects on technical white-collar workers , 1981 .

[19]  J.-M. Henrioud,et al.  APPLYING EQUAL PILES APPROACH TO DISASSEMBLY LINE BALANCING PROBLEM , 2005 .

[20]  Paul Valckenaers,et al.  HMS - Holonic Manufacturing Systems Test Case (IMS Project) , 1997, ICEIMT.

[21]  Andrew B. Whinston,et al.  Foundations of Decision Support Systems , 1981 .

[22]  Ralph H. Sprague,et al.  A Framework for the Development of Decision Support Systems , 1993 .

[23]  John R. Beaumont,et al.  Control and Coordination in Hierarchical Systems , 1981 .

[24]  Hans Wortmann,et al.  Information Infrastructure Systems for Manufacturing , 1997, IFIP — The International Federation for Information Processing.

[25]  F. G. Filip Towards more humanized real time decision support systems , 1995 .

[26]  Constantin-Bala Zamfirescu An Agent-Oriented Approach for Supporting Self- Facilitation for Group Decisions , 2003 .

[27]  Gheorghe Tecuci,et al.  Mixed-Initiative Assumption-Based Reasoning for Complex Decision-Making , 2007 .

[28]  Lisanne Bainbridge,et al.  Ironies of automation , 1982, Autom..

[29]  Amitava Dutta,et al.  Integrating AI and optimization for decision support: a survey , 1996, Decis. Support Syst..

[30]  Hendrik Van Brussel,et al.  On the design of emergent systems: an investigation of integration and interoperability issues , 2003 .

[31]  M. Mesarovic,et al.  Theory of Hierarchical, Multilevel, Systems , 1970 .

[32]  Adrian V. Gheorghe Risks, vulnerability, sustainability and governance: a new landscape for critical infrastructures , 2004, Int. J. Crit. Infrastructures.

[33]  John R. Beaumont,et al.  Large-Scale Systems: Modeling and Control , 1983 .

[34]  A. Bosman,et al.  Relations between specific decision support systems , 1987, Decis. Support Syst..

[35]  H. Van Dyke Parunak Practical and Industrial Applications of Agent-Based Systems , 1998 .

[36]  László Monostori,et al.  From plant and logistics control to multi-enterprise collaboration , 2006, Annu. Rev. Control..

[37]  Florin G. Filip,et al.  Supporting self-facilitation in distributed group decisions , 2002, Proceedings. 13th International Workshop on Database and Expert Systems Applications.

[38]  Steven L. Alter,et al.  Decision support systems : current practice and continuing challenges , 1980 .

[39]  M. Höpf,et al.  Holonic manufacturing systems , 1997 .

[40]  M. Cioca,et al.  Spatial [Elements] Decision Support System Used in Disaster Management , 2007, 2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference.

[41]  Ralph H. Sprague,et al.  DSS in context , 1987, Decis. Support Syst..

[42]  Daniel J. Power,et al.  Decision Support Systems: Concepts and Resources for Managers , 2002 .

[43]  Thomas B. Sheridan,et al.  Telerobotics, Automation, and Human Supervisory Control , 2003 .

[44]  A Koestler,et al.  Ghost in the Machine , 1970 .