An active intelligent decision support system — Architecture and simulation

Development and implementation of decision support systems to support intelligent decision making is an area of research that has gained in importance in recent years. Due to the increased complexity of decision making, active involvement of the user and the computer in an intelligent way is necessary in the decision process. This paper presents issues in the design of an active intelligent decision support system (IDSS), develops an architectural model based on cooperative distributed problem solving, and performs a simulation of the system using object oriented programming for an example application in airfleet control.     

物流配送中心综合决策支持系统的设计

近年来,随着物流配送中心自身的不断发展,配送技术的日益改进,配送中心业务量的不断增大,仅仅靠以业务处理为主的MIS难以胜任管理者日益增长的辅助决策需要。因此,建立物流配送中心的决策支持支持系统成为必然要求。以某物流配送中心决策支持系统建设为背景,设计了物流配送中心综合决策支持系统的总体功能模块和系统的集成架构并详细介绍了数据库数据仓库、知识库、模型库的设计。     

A Dss Classification Model for Research in Human Resource Information Systems

Any field of study can benefit from a framework into which past and present research can be classified and from which potential research hypotheses can be generated. This article develops a decision support system classification model for research in human resource information systems (HRIS), a model that can then be utilized for evaluating whether an HRIS does provide a competitive advantage for an organization in today's ever-changing, fast-paced, global business environment. As background for this article, the topics of managerial decision making, decision support systems, human resource information systems, and the principle of competitive advantage are reviewed.     

Organizational decision support systems

Decision support systems have traditionally been discussed within the context of individual or group decision making. In this paper we study decision support systems from an organizational perspective. We propose a framework for designing an organizational decision support system that is based on a network of knowledgebased systems. Nodes of this network interact with each other, as well as various other organizational systems, to provide comprehensive decision support. This network is also utilized to provide effective support for formal multi-participant decision making.     

一种继电保护在线状态检修辅助决策信息系统的PIM模型

分析目前电网继电保护状态评价与辅助决策系统的现状,指出缺乏统一建模是相关系统在架构上的主要缺陷,提出根据模型驱动体系结构的核心思想,建立继电保护状态评价与辅助决策全过程的平台无关信息模型(PIM)。首先对继电保护状态评价与辅助决策的全过程进行抽象总结,然后通过对状态量采集和存储、状态评价和辅助决策这3个过程分别进行分析和建模,最终给出继电保护在线状态评价与辅助决策系统PIM模型的参考架构。     

Evaluation of decision support systems in medicine

Evaluation deals with the measurement or judgement of system characteristics and with comparison of these with the frame of reference. Evaluation of medical decision support systems is important because these systems are planned to support human decision making in tasks where information from different sources is combined to support clinicians' decisions concerning diagnosis, therapy planning and monitoring of the disease and treatment processes. As the field of decision support systems is still relatively unexplored, standards or generally accepted methodologies are not yet available for evaluation. Evaluation of medical decision support systems should be approached from the perspectives of knowledge acquisition, system development life-cycle and user-system integrated environment.     

基于Agent的决策支持系统

针对传统决策支持系统的局限性以及决策支持问题的复杂性，本文开发了一个基于Agent的决策支持系统。系统内的多个Agent通过Agent信息路由器通讯交流，相互合作,共同完成决策支持任务。     

Adaptive decision support systems

The effectiveness of decision support systems (DSS) is enhanced through dynamic adaptation of support to the needs of the decision maker, to the problem, and to the decision context. We define this enhanced DSS as adaptive decision support systems (ADSS) and propose its architecture. In an ADSS, the decision maker controls the decision process. However, the system monitors the process to match support to the needs. The proposed architecture evolves from the traditional DSS models and includes an additional intelligent‘Adaptation’ component. The ‘Adaptation’ component workd with the data, model, and interface components to provide adaptive support. The architecture also integrates enhancements proposed in the past research. In this paper, we have illustrated the proposed architecture with two examples, a prototype system, and results from a preliminary empirical investigations     

A Dss Classification Model for Research in Human Resource Information Systems

Abstract

Any field of study can benefit from a framework into which past and present research can be classified and from which potential research hypotheses can be generated. This article develops a decision support system classification model for research in human resource information systems (HRIS), a model that can then be utilized for evaluating whether an HRIS does provide a competitive advantage for an organization in today's ever-changing, fast-paced, global business environment. As background for this article, the topics of managerial decision making, decision support systems, human resource information systems, and the principle of competitive advantage are reviewed.     

综合决策支持系统框架的研究

文中在对现有的几种决策支持系统框架结构进行分析研究的基础上,将数据仓库(DW)、数据挖掘(DM)、联机分析处理(OLAP)、数据库(DB)、模型库(MB)和知识库(KB)集成,引入了综合决策支持系统(SDSS)框架的概念。文中详细阐述了该框架各组成部分的功能及相互关系,总结了此种框架的基本特征及开发实现的关键技术。     

Rationality in Information Systems Support to Decision Making

Management information systems serve business organizations by providing information for decision making. Various types of systems serve different types of decision contexts. The philosophic basis of information system support is discussed. The rational (or normative) philosophy is widely used, and appears in business theory in the form of agency theory and transaction cost analysis. While this approach has been valuable in some contexts, there are other contexts where the rational approach has limited in utility for real business decision making. Decision makers need to consider subjective factors to enable them to cope with the high levels of uncertainty, incomplete understanding, and imperfect data typical of dynamic open systems. There are alternative philosophies upon which to base decision-making that are appropriate for specific decision contexts. Churchman identified empirical, multi-perspective frameworks, dialectic, and cause-and-effect inquiring systems as alternatives to the rational (normative) system. A number of information system tools, such as decision support systems, expert systems, and group support systems can be supported by models based on philosophies other than rational models. A more empirically based philosophy, with decision-makers balancing hypothesis generation and observations of performance, is often more appropriate. The relationship between Churchman's inquiring systems and information system types are discussed.     

Decision support requirements in flexible manufacturing

Flexible manufacturing systems are being installed by many organizations in an effort to improve productivity. Because efficient operation of these systems is such a complex task, their capacity is often underutilized. The concept of computer-based decision support systems promises to remedy the situation. This paper defines the components of a decision support system which will enable the user to get the maximum benefit from a flexible manufacturing system. The structure of this decision support system parallels the organizational activities involved in running the flexible manufacturing system. This structure should be implemented using appropriate hardware and software components.     

Predicting adequacy of vancomycin regimens: A learning-based classification approach to improving clinical decision making

Clinicians' drug regimen decision making is critical, particularly when involving high-alert medications. In this study, we use decision-tree induction C4.5 and a backpropagation neural network to construct decision support systems for predicting the regimen adequacy of vancomycin, a glycopeptide antimicrobial antibiotic effective for Gram-positive bacterial infections. We comparatively evaluate the respective systems using a total of 987 clinical vancomycin cases collected from a major tertiary medical center in southern Taiwan. We supplement each system using Bagging and then examine the predictive power of the extended system. Overall, our evaluation results show the overall accuracy of the decision support system based on C4.5 or the neural network to be significantly higher than that of the benchmark one-compartment pharmacokinetic model. Use of Bagging can considerably improve the effectiveness of each system across different performance measures, particularly for cases of decision classes in which the base systems (i.e., without Bagging) perform modestly. Taken together, our evaluation results seem to favor the use of Bagging to enhance the performance of decision support systems constructed using decision-tree induction C4.5.     

基于Agent的智能决策支持系统开发与应用

针对传统决策支持系统的局限性,该文提出了一个基于Agent的智能决策支持系统开发方案。利用界面Agent、信息Agent、移动Agent、协作Agent来实现系统的智能部件,多Agent通过协作Agent信息路由器进行协作和交互,共同完成决策支持任务。并将该模型应用于草业信息管理决策支持系统中,系统运行结果证明了模型的有效性和科学性。     

Pluralistic multi-agent decision support system: a framework and an empirical test

Recent research in decision support systems (DSSs) has focused on building active cooperative intelligent systems. Research in agent-based decision support is a promising stream in this direction. This paper proposes a framework for a pluralistic multi-agent decision support system (MADSS). The distinguishing feature of the proposed approach is its organization around human decision making process. The framework builds upon the decision support pyramid with agents organized into groups according to the phases of the problem solving model. We outline the design principles and develop architecture for MADSS. The framework is illustrated through an investment MADSS prototype. The results of the empirical test are presented.     

Fuzzy logic-based decision support system for automating ergonomics risk assessments

Workers in the modular construction industry are frequently exposed to ergonomic risks, which may lead to injuries and lower productivity. In light of this, researchers have proposed a number of ergonomics risk assessment methods to identify design flaws in work systems, thereby reducing ergonomic discomfort and boosting workplace productivity. However, organizations often disregard ergonomics risk assessments due to a lack of convenient tools and knowledge. Therefore, this study proposes a fuzzy logic-based decision support system to help practitioners to automatically and comprehensively assess the ergonomic performance of work systems. For comprehensive assessment of ergonomic risk, the proposed decision support system considers physical, environmental, and sensory factors. Specifically, the decision support system comprises eight fuzzy expert systems that output a composite risk score, called an “ergonomic risk indicator”, that indicates the overall level of ergonomic risk present in a given work system. The performance of the proposed decision support system is then evaluated using a real-world case study in a modular construction facility by comparing the results of the decision support system with the facility's occupational injury reports. The results prove the effectiveness of the decision support system. Overall, the decision support system is capable of generating a composite risk score, the ergonomic risk indicator, and the proposed high-level architecture and design represent significant contributions for the enhancement of health and safety in the modular construction industry.     

A knowledge-based decision support system for the management of parts and tools in FMS

Flexible manufacturing systems (FMS) are very complex systems with large part, tool, and information flows. The aim of this work is to develop a knowledge-based decision support system (KBDSS) for short-term scheduling in FMS strongly influenced by the tool management concept to provide a significant operational control tool for a wide range of machining cells, where a high level of flexibility is demanded, with benefits of more efficient cell utilization, greater tool flow control, and a dependable way of rapidly adjusting short-term production requirements. Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing. In this context, this paper proposes three knowledge-based models to ease the decision making process: an expert production scheduling system, a knowledge-based tool management decision support systems, and a tool management fault diagnosis system. The entire system has been created in a hierarchical manner and comprises more than 400 rules. The expert system (ES) was implemented in a commercial expert system shell, Knowledge Engineering System (KES) Production System (PS).     

销售利润决策支持系统的开发

在系统需求分析的基础上完成了销售利润决策支持系统的开发，解决了销售利润决策中涉及的许多半结构化问题。该系统总体设计为八个子系统，融合了辅助决策、数据库和管理信息系统的相关技术。在系统实现过程中对决策支持系统的模型库、数据库和方法库的接口问题进行了探讨与实践。