Decision Support System Narrative Essay Example

a sample application for the web-based DES.
6. Conclusion and future work.

Before delving into the details, it is necessary to define decision support systems. Decision support systems are computer technology solutions that aid in complex decision making and problem solving. These systems incorporate interactive capabilities to address the complexity and uncertainty of decision problems (Shim et al.[17]).The purpose of this text is to enhance understanding and knowledge about decision problems by using models and data processing. This allows for combining personal judgment with information provided by these tools. The classic design of a Decision Support System (DSS) consists of database management capabilities, access to internal and external data, information, and knowledge, powerful modeling functions accessed through a model management system, as well as user interfaces for interactive communication. DSSs are computer-based systems that help decision makers solve problems and make decisions using data and models. These systems aid in solving nonprogrammer, unstructured problems and have an interactive query facility with an easy-to-learn and use query language. DSSs assist managers in their decision processes for semiconductors or unstructured tasks, supporting their judgment rather than replacing it.The objective of the text is to enhance decision effectiveness rather than decision efficiency. According to [8], there are five categories of decision support systems (DES). Communications-Driven DES utilizes network and communications technologies to promote collaboration and communication. Data-Driven DES focuses on accessing and manipulating internal and sometimes external company data, as well as providing comprehensive document retrieval and analysis. Knowledge-Driven DES aims to offer suggestions or recommendations to managers using specialized provisioning expertise on personal computer systems. Model-Driven DES or Model-oriented DES prioritizes accessing and manipulating various models such as

statistical, financial, optimization, and/or simulation models. Simpler statistical and analytical tools provide basic functionality. A Web-based Decision Support System employs web technologies to enhance the capability of decision support systems through decision models, On-line Analysis Processing (OLAP), and data mining tools. These tools enable the "standardized" publishing and sharing of decision resources on the Internet.In a web-based decision support system, all decision support related operations are performed on a network server in order to benefit from platform independence, shorter learning curves for already familiar users with the Web tools and web navigation, lower software distribution costs, ease of performing system updates and "risibility' of decision modules and information on the Internet through standardized protocols and formats [8]. According to [5], the importance of using Web-based DES originates from the growing amount of available information that should be identified, controlled and accessed remotely using web based tools to support risibility of integrated decision modules. Using such systems, an enterprise can create survey software, Web based arms, build document-driven DES for requests and approvals. They help global enterprises manage and improve decision processes through improved efficiency, better process control, improved customer service, more flexible re-design, and streamlining and simplification of business processes. Using Web-based DES, decision-makers can share open decision modules on the Internet using standardized protocols such as HTTP, and a standardized format like XML or DAML. According to [16], Web-based systems are regarded as «platforms of choice" for delivering decision support while taking into account many technical, economic and social considerations.The shift towards web-based DES involves a transition from DES generators, which have limitations in application development and flexibility, to integrated cross-application orientations that prioritize

the reuse of applications and components.

With the deployment of web capabilities, multiple knowledge bases and processing techniques can be utilized. The availability of a wide array of web-based tools, techniques, and technologies has impacted the design of decision support systems. The use of web tools is reshaping how information components and decision modules are described, influencing the physical and logical design of the DES, as well as the visualization, curability, and development life cycle of decision modules.

Consequently, the underlying architecture for web-based DES has evolved from mainframes to client-server systems, and now to web and network technology-based distributed systems. These systems enable the integration of substantial amounts of data and decision support tools from diverse multidisciplinary sources. They provide value-added information through the use of knowledge discovery and data mining tools.

Recent research in web-based decision support systems focuses on two areas: architectures and technologies, and applications and implementations.

Several articles have focused on various specific topics related to Web-based decision support systems (DES). For example, Skulks and Paul [12] reviewed the use of Web-based simulation, while Kerosene and Normal [10] discussed Webbed negotiation support. Regarding architectures and technologies, a number of articles discuss issues such as frameworks, usability, and other technology-related topics that are generally applicable to Web-based DES. Gregg et al.[6] proposed a DES metadata model for distributing decision support systems on the Web. On the other hand, Bahrain and Chuddar [1] conducted an empirical study to examine customer satisfaction with a Web-based decision support system. Lyre et al.[9] focused on model management in a computing environment where enterprise data and models are distributed. Gunter et al.[7] suggested the use of Structured Service Models

that employ a variant of structured modeling to help users find information resources available as online services within an Intranet. Ghana and Goddard [22] applied Software Architectures to the design of Web-based DES. Miter and Valence [13] provided an overview of Webbed optimization for model-driven decision support, discussing two paradigms (ASP and e-Services) as well as technology issues for an e-Services model. In terms of applications and implementations, there are numerous reports of case studies and prototype applications of Web-based DES by researchers and vendors, including Kohl et al.

[1 1] described a case study of a Web-based decision support system (DES) called the Physician Profiling System (UPS).

Angina and Watt [14] developed and implemented a Web-based DES that utilized a fuzzy set theory model for risk analysis in e-commerce development. Dong et al. [4] created a Web-based DES framework for portfolio selection. Cassandra [19] identified key issues in managing service contracts and developed a prototype to aid in a manager's planning process. Ray [1 5] presented a case study showcasing the implementation of Web-based decision support technologies. Delve et al. [3] built the Movie Forecast Guru, a Web-based DES, to assist decision makers in the movie industry. Numerous additional case studies exist regarding the deployment of Web-based decision support systems. For instance, Summary and Meyer [18] documented the development of a Spatial DES prototype for the City of Columbia, Missouri. 4 Contribution Given the diverse data sources and corresponding decision support tools, designing, specifying, and implementing a Web-based DES in a distributed environment remains an ongoing research challenge [22].

Firstly, a Web-based DES often encounters difficulties as the data and related tools were not originally

designed to work together. Traditional DES design methods lack the ability to facilitate their organization in a hierarchical view and specify the software architectures of a Web-based DES formally.The text discusses the use of web and network technology to locate data and decision support tools from different areas on computers distributed over a network. In a distributed environment, a web-based Decision Support System (DES) requires a framework to manage and integrate the data and tools effectively. Additionally, the text mentions a novel approach for decision making that involves an agent architecture-based model. This model presents a multicultural DES that can address uncertainty problems in dynamic production system scheduling. The model utilizes negotiation contracts based on the agent approach, which allows easy access to tasks executed by Integrated Stations of Production (ISP) agents. The text also introduces an agent-based Web DES aimed at helping users solve resource failure problems in an industrial estate through a web service accessed within an intranet. The solution involves negotiation between ISP agents and other web-based agents. When a resource failure occurs, the ISP agent checks the workshop's resources and contacts web-based agents for decision-making assistance in resolving the failure. A MAUL diagram is provided to illustrate the feasibility of the proposed idea.The proposed model includes Enterprise 1, Enterprise 2, web Site 1, web Site 2, Web Site n, Web Service 1, and Enterprise n, as well as various agents such as Resource Agent, Proposal Agent, and Analyzer Agent. A diagram of the general architecture is shown in Fig.L.

In the scenario for the proposed model, the Analyzer Agent is responsible for analyzing and filtering breakdowns. The Resource Agent seeks the

reference of the broken down resource, researching and determining if a solution can be found. If a solution is found, the breakdown is repaired and the resource is ordered. Fig.2 shows the communication between agents in a sequence diagram.

The structure of the Analyzer Agent includes functional modules such as analysis module, proposal generator module, database, knowledge base, rules base, filter, and interface. The analysis module serves as the core of this architecture by using data input from the database, knowledge from the knowledge base, and rules from the rules base to analyze and filter breakdowns. The interface module manages information exchanges between the Analyzer Agent and other agents. During problem resolution, the analyzer agent requests the resource agent to search for resource references on the web.The agent structure for the analyzer (Fig.3) and the proposal (Fig.5.2) involves various modules including the database interface module, knowledge base module, analysis module, rules base module, and proposals generator module. The analyzer agent first locates the reference of a resource on the Web, then requests the proposal agent to conduct advanced research on the Web regarding the resource breakdown. The proposal agent consists of several functional modules such as research module, solutions generator module, database, knowledge base, rules base, and web data launching module. It generates multiple solutions based on the breakdown identified. The interface module facilitates information exchange between the proposal agent and other agents. The proposal agent structure is depicted in Figure 5.2.

In a sample application of Web-DES, agents interact to solve a resource allocation problem for a company wanting to create a custom computer installation for a client. This scenario requires decision-making, as shown in

the practical situation illustrated in both Figure 5 and Figure 6. Figure 5 depicts the simulation function, while Figure 6 showcases decision-making in action.The Resource 7 Conclusion presents a simulation of a breakdown in a Web-based DES. This DES utilizes the Web as a means to access and utilize the underlying DES. Implementing a distributed version of the DES is also essential for a successful Web-based DES. Our multi-agent approach integrates agents into the Web-based DES to automate tasks, facilitate indirect management, and minimize direct manipulation. Agents are used to address significant solutions, while communication capabilities are crucial for the system's operation. Additional work is required to develop coordination protocols between agents and improve decision-making support and coordination activities. The architecture of the proposed Web-based DES is currently being developed.