Real-time Decision Support System Research Articles

An expert system for selecting manufacturing workers for training

Intelligent real-time decision support systems are specialized domain-based tools for management. The intelligent component of decision support systems (DSS) assumes a certain level of human expertise that can be used to advise the manager on certain decision issues. In the domain of training, emphasis has been on tutoring and learning system developments. In the manufacturing industries, the problem of selecting employees for training is time consuming and belongs to a special class of multiattribute decision making. Although many manufacturing concerns have developed and implemented commendable training programs, there are still concerns of under training or overtraining based on the selection process of the employees. This paper describes a prototype knowledge-based training selection system that will identify and weight trainability factors and advise the manager on the employee trainability level. The simulation prototype, known as TSES (Trainability Selection Expert System), is a concept-driven expert system that evaluates the user subjective input data and gives some fuzzy ranking to aid management decisions. TSES behaves as a diagnostic “expert” in determining the selection and prioritizing of employee data.

The real-time on-line decision support system RODOS for off-site emergency management / Das Echtzeit- und On-line-Entscheidungshilfesystem RODOS für den externen Katastrophenschutz

The project RODOS aims at the development of an integrated and comprehensive real-time on-line decision support system for off-site emergency management of nuclear accidents in Europe, applicable to the vicinity of the accident and its early phase up to far distant areas and later stages. As a joint venture of 18 institutions in the European Union, in close cooperation with institutions in Russia, Belarus, Ukraine and east-central Europe, the project is to provide the methodological basis, develop models, collect data, and install the hardware and software framework of the RODOS system

Atmospheric Dispersion Models and Pre-Processing of Meteorological Data for Real-time Application

RODOS is a real-time and on-line decision support system for assisting emergency response in the case of a nuclear emergency. The system is presently under development within the CEC Radiation Protection Programme as a joint venture between several European institutes. This paper identifies, ranks and selects a series of suitable local scale atmospheric flow and dispersion models for RODOS, covering a variety of release types, terrain types and atmospheric stability conditions. The identification and ranking of suitable models is based on a discussion of principal modelling requirements, scale considerations, model performance and evaluation records, computational needs, user expertise, and type of sources to be modelled. Models suitable for a given accident scenario are chosen from this hierarchy in order to provide the dose assessments via the dispersion module. A forecasting feasibility for estimation of possible dose assessments is proposed by on-line connecting the RODOS system via computer networks to national or international numerical weather forecast centres. Local meteorology is introduced into RODOS via a menu-driven 'Pre-processor for Atmospheric Dispersion' module. The pre-processor provides the flow and dispersion models with on-site wind and atmospheric stability measures.

Atmospheric Dispersion Models and Pre-Processing of Meteorological Data for Real-time Application

RODOS is a real-time and on-line decision support system for assisting emergency response in the case of a nuclear emergency. The system is presently under development within the CEC Radiation Protection Programme as a joint venture between several European institutes. This paper identifies, ranks and selects a series of suitable local scale atmospheric flow and dispersion models for RODOS, covering a variety of release types, terrain types and atmospheric stability conditions. The identification and ranking of suitable models is based on a discussion of principal modelling requirements, scale considerations, model performance and evaluation records, computational needs, user expertise, and type of sources to be modelled. Models suitable for a given accident scenario are chosen from this hierarchy in order to provide the dose assessments via the dispersion module. A forecasting feasibility for estimation of possible dose assessments is proposed by on-line connecting the RODOS system via computer networks to national or international numerical weather forecast centres. Local meteorology is introduced into RODOS via a menu-driven 'Pre-processor for Atmospheric Dispersion' module. The pre-processor provides the flow and dispersion models with on-site wind and atmospheric stability measures.

Optimizing disaster relief: Real-time operational and tactical decision support

We introduce a real-time decision support system which uses optimization methods, simulation, and the judgement of the decision maker for operational assignment of units to tasks and for tactical allocation of units to task requirements. The system, named ARES for the Greek god of war, accommodates a high degree of detail in the logistics of unit movements during operations, yet separates the assignment and allocation activities in a fashion which naturally accommodates human intervention and judgement—ARES is designed to assist the decision maker, not to replace him. ARES is demonstrated with a hypothetical scenario constructed for 14 Engineering Battalions of the Hellenic Army which are assigned 20 tasks employing 25 resource types in repairing major damage to public works following a great earthquake. (This hypothetical data was prepared prior to the earthquake in Kalamata near Athens on 13 September, 1986, and exhibits uncanny, but coincidental, resemblance to that real situation.) ARES is designed for use in real time, and quick data preparation is aided by the provision from published sources of standard data for many foreseeable tasks; this data can be quickly accessed via visual icons on a computer screen and customized for the actual work at hand. © 1993 John Wiley & Sons, Inc.

Resource configuration and allocation-a case study of constrained heuristic search

Constrained heuristic search techniques are applied to the problems of product configuration and inventory planning. The architecture of Coral, an interactive, real-time decision support system that maximizes the total number of products requested, given one or more substitutable configurations, is presented. Coral gives inventory managers a tool for managing and allocating component inventories, thus maximizing the number of complete orders. Coral treats configuration and allocation as constraint-satisfaction and optimization problems in which constraints guide the problem solving. The configuration, resource allocation, and performance of a histogram-based input interface to enter order-composition specifications and a tabular report to enter definitions of ammunition rounds into Coral are described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

FC-VS: a decision support system for flood control in multireservoir systems

The paper presents a software package FC-VS (Flood Control - Vistula System) designed as a real-time Decision Support System for the control centre of multireservoir water system in Southern Poland. This is an implementation of a two-level control structure for the optimal flood operation of river - reservoir systems. The natural hierarchy of the decision units, i.e., the control centre and operators of the reservoirs is preserved. The FC-VS system helps the central dispatcher by proposing him the values of special coordinating parameters for modifying release decisions of local reservoirs operators. The aim of the structure is to minimize damages created by a flood wave passing through a river-basin. FC-VS can be also used for training purposes using historical data. Some simulation results in the final part of the article.

FC-ROS — Decision Support System for reservoir operators during flood

The article presents a special software package FC-ROS (Flood Control — Reservoir Operator's System) designed as a real-time Decision Support System for reservoir operators during flood. The system helps the operator by showing him all important data as well as several decision proposals (i.e. release patterns) resulting from various control algorithms. These algorithms were projected under the assumption, that the basic aim in single reservoir management during flood is minimization of damages evoked by high water levels downstream the reservoir. Before making the decision, the operator can analyze the consequences of each proposal by simulation. FC-ROS can be also used for training purposes basing on historical data. Some results of a training session are presented in the final part of the article.

状況対応意思決定支援システムに関する一考察

状況対応意思決定支援システムに関する一考察

A decision support system for dynamic truck dispatching

Abstract The feasibility of developing and implementing a real-time Decision Support System (DSS) on a microcomputer to assist line managers in making decisions, which have many subjective and intangible constraints, is demonstrated. A dynamic truck dispatching system was chosen as a prototype example. The results of the research presented here are twofold. First, insight was gained in how tasks should be divided between the computer and the human operator and in the required colorgraphics interface between them in complex decision making processes. Second, a prototype DSS for a real-time vehicle dispatching system was developed on a microcomputer based upon these insights. The DSS was designed to accommodate all the characteristics of a large corporation's national dispatch system using contract carriers.

Rainfall Estimation And Real-time ReservoirOperation With Neural Network And FuzzyInference

The aim of this study is to propose the real-time decision support system of storage reservoir introducing the advanced artificial intelligent methodologies of the neural network and the fuzzy theory.