Model Management and Solvers for Decision Support

2008 ◽  
pp. 231-258 ◽  
Author(s):  
Ting-Peng Liang ◽  
Ching-Chang Lee ◽  
Efraim Turban
Keyword(s):  
Decision Support ◽  
Model Management

The Changing Structure of Decision Support Systems Research

2010 ◽  
pp. 318-342
Author(s):  
Sean Eom
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Group Support Systems ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Model Management ◽  
Intellectual Structure ◽  
Research Areas ◽  
Systems Research

This chapter extends an earlier benchmark study (Sean B. Eom, 1995) which examined the intellectual structure, major themes, and reference disciplines of decision support systems (DSS) over the last two decades (1960-1990). Factor analysis of an author cocitation matrix over the period of 1990 through 1999 extracted 10 factors, representing 6 major areas of DSS research: group support systems, DSS design, model management, implementation, and multiple criteria decision support systems and five contributing disciplines: cognitive science, computer supported cooperative work, multiple criteria decision making, organizational science, and social psychology. We have highlighted several notable trends and developments in the DSS research areas over the 1990s.

Intelligent Decision Support System in Damage Control of Damaged Ship

2013 ◽  
Vol 694-697 ◽  
pp. 2476-2482
Author(s):  
Ang Li ◽  
Jin Yun Pu
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Damage Control ◽  
Model Management ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
Intelligent Decision Support ◽  
Damaged Ship

An intelligent decision support system in damage control of damaged ship combined with data mining is constructed in this paper. The human-computer interaction subsystem, the database management subsystem, the model management subsystem and the knowledge management subsystem are introduced in detail and some programming technologies of the system are displayed. The pivotal technology of the realization of this system is discussed briefly at last.

CATEGORIZATION OF DISASTER DECISION SUPPORT NEEDS FOR THE DEVELOPMENT OF AN INTEGRATED MODEL FOR DMDSS

2008 ◽  
Vol 07 (01) ◽  
pp. 115-145 ◽  
Author(s):  
SOHAIL ASGHAR ◽  
DAMMINDA ALAHAKOON ◽  
LEONID CHURILOV
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Disaster Management ◽  
Integrated Model ◽  
Model Management ◽  
Model Integration ◽  
Management Decision ◽  
Support Needs ◽  
Management Area ◽  
Disaster Scenario

The wide variety of disasters and the large number of activities involved have resulted in the demand for separate Decision Support System (DSS) models to manage different requirements. The modular approach to model management is to provide a framework in which to focus multidisciplinary research and model integration. A broader view of our approach is to provide the flexibility to organize and adapt a tailored DSS model (or existing modular subroutines) according to the dynamic needs of a disaster. For this purpose, the existing modular subroutines of DSS models are selected and integrated to produce a dynamic integrated model focussed on a given disaster scenario. In order to facilitate the effective integration of these subroutines, it is necessary to select the appropriate modular subroutine beforehand. Therefore, subroutine selection is an important preliminary step towards model integration in developing Disaster Management Decision Support Systems (DMDSS). The ability to identify a modular subroutine for a problem is an important feature before performing model integration. Generally, decision support needs are combined, and encapsulate different requirements of decision-making in the disaster management area. Categorization of decision support needs can provide the basis for such model selection to facilitate effective and efficient decision-making in disaster management. Therefore, our focus in this paper is on developing a methodology to help identify subroutines from existing DSS models developed for disaster management on the basis of needs categorization. The problem of the formulation and execution of such modular subroutines are not addressed here. Since the focus is on the selection of the modular subroutines from the existing DMDSS models on basis of a proposed needs classification scheme.

Intelligent Information Systems

2011 ◽  
pp. 2118-2125
Author(s):  
John Fulcher
Keyword(s):  
Decision Support ◽  
Information Systems ◽  
Management System ◽  
Knowledge Bases ◽  
Model Management ◽  
The People ◽  
Perform Sensitivity Analysis ◽  
1960S And 1970S ◽  
Intelligent Information ◽  
The 1960S

Information Systems (IS), not surprisingly, process information (data + meaning) on behalf of and for the benefit of human users. Information Systems comprise the basic building blocks shown in Figure 1, and as such can be likened to the familiar Von Neumann computer architecture model that has dominated computing since the mid 20th Century. In practice, IS encompass not just computer system hardware (including networking) and software (including DataBases), but also the people within an organization (Stair & Reynolds, 1999). Information Systems are ubiquitous in today’s world–the so-called “Digital Age”–and are tailor-made to suit the needs of many different industries. The following are some representative application domains: • Management Information Systems (MIS) • Business IS • Transaction processing systems (& by extension, eCommerce) • Marketing/Sales/Inventory IS (especially via the Internet) • Postal/courier/transport/fleet/logistics IS • Geographical Information System (GIS)/Global Positioning Satellite (GPS) systems • Health/Medical/Nursing IS The roles performed by IS have changed over the past few decades. More specifically, whereas IS focussed on data processing during the 1950s and 1960s, management reporting in the 1960s and 1970s, decision support during the 1970s and 1980s, strategies and end user support during the 1980s and 1990s, these days (the early years of the 21st Century) they focus more on global Internetworking (O’Brien, 1997). Accordingly, we nowadays find extensive use of IS in e-business, decision support, and business integration (Malaga, 2005). Let us take a closer look at one of these–Decision Support Systems. A DSS consists of (i) a (Graphical) User Interface, (ii) a Model Management System, and (iii) a Data Management System (comprising not only Data/Knowledge Bases but also Data Warehouses, as well as perhaps incorporating some Data Mining functionality). The DSS GUI typically displays output by way of text, graphs, charts and the like, enabling users to visualize recommendations/advice produced by the DSS. The Model Management System enables users to conduct simulations, perform sensitivity analysis, explore “what-if” scenarios (in a more extensive manner than what we are familiar with in spreadsheets), and so forth.

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