Leveraging simulation practice in industry through use of desktop grid middleware

This chapter focuses on the collaborative use of computing resources to support decision making in industry. Through the use of middleware for desktop grid computing, the idle CPU cycles available on existing computing resources can be harvested and used for speeding-up the execution of applications that have “non-trivial” processing requirements. This chapter focuses on the desktop grid middleware BOINC and Condor, and discusses the integration of commercial simulation software together with free-to-download grid middleware so as to offer competitive advantage to organizations that opt for this technology. It is expected that the low-intervention integration approach presented in this chapter (meaning no changes to source code required) will appeal to both simulation practitioners (as simulations can be executed faster, which in turn would mean that more replications and optimization is possible in the same amount of time) and the management (as it can potentially increase the return on investment on existing resources)

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

THE ROLE OF COGNITIVE APPORTIONMENT IN INFORMATION SYSTEMS

As the number of information system users increases, we are witnessing a related increase in the complexity and the diversity of their applications. The increasing functional complexity amplifies the degree of functional and technical understanding required of the user to make productive use of the application tools. Emerging technologies, increased and varied user interests and radical changes in the nature of applications give rise to the opportunity and necessity to re-examine the proper apportionment of cognitive responsibilities in human/system interaction. Examples illustrate the opportunities afforded by such an examination. A framework is presented that illustrates many of the tradeoffs that occur in a reapportionment activity. A knowledge-based architecture is proposed to facilitate both static and dynamic reapportionment decisions

Using spreadsheets as learning tools for neural network simulation

The article supports the need for training techniques for neural network computer simulations in a spreadsheet context. Their use in simulating artificial neural networks is systematically reviewed. The authors distinguish between fundamental methods for addressing the issue of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools for neural network simulation, application of third-party add-ins to spreadsheets, development of macros using embedded languages of spreadsheets, use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins, and On the article, methods for creating neural network models in Google Sheets, a cloud-based spreadsheet, are discussed. The classification of multidimensional data presented in R. A. Fisher's "The Use of Multiple Measurements in Taxonomic Problems" served as the model's primary inspiration. Discussed are various idiosyncrasies of data selection as well as Edgar Anderson's participation in the 1920s and 1930s data preparation and collection. The approach of multi-dimensional data display in the form of an ideograph, created by Anderson and regarded as one of the first effective methods of data visualization, is discussed here.The article supports the need for training techniques for neural network computer simulations in a spreadsheet context. Their use in simulating artificial neural networks is systematically reviewed. The authors distinguish between fundamental methods for addressing the issue of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools for neural network simulation, application of third-party add-ins to spreadsheets, development of macros using embedded languages of spreadsheets, use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins, and On the article, methods for creating neural network models in Google Sheets, a cloud-based spreadsheet, are discussed. The classification of multidimensional data presented in R. A. Fisher's "The Use of Multiple Measurements in Taxonomic Problems" served as the model's primary inspiration. Discussed are various idiosyncrasies of data selection as well as Edgar Anderson's participation in the 1920s and 1930s data preparation and collection. The approach of multi-dimensional data display in the form of an ideograph, created by Anderson and regarded as one of the first effective methods of data visualization, is discussed here

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Is Trust Always Better than Distrust? The Potential Value of Distrust in Newer Virtual Teams Engaged in Short-term Decision-Making

The debate on the benefits of trust or distrust in groups has generated a substantial amount of research that points to the positive aspects of trust in groups, and generally characterizes distrust as a negative group phenomenon. Therefore, many researchers and practitioners assume that trust is inherently good and distrust is inherently bad. However, recent counterintuitive evidence obtained from face-to-face (FtF) groups indicates that the opposite might be true; trust can prove detrimental, and distrust instrumental, to decision-making in groups. By extending this argument to virtual teams (VTs), we examined the value of distrust for VTs completing routine and non-routine decision tasks, and showed that the benefits of distrust can extend to short-term VTs. Specifically, VTs seeded with distrust significantly outperformed all control groups in a non-routine decision-making task. In addition, we present quantitative evidence to show that the decision task itself can significantly affect the overall levels of trust/distrust within VTs. In addition to its practical and research implications, the theoretical contribution of our study is that it extends to a group level, and then to a VT setting, a theory of distrust previously tested in the psychology literature in the context of completing non-routine and routine decision tasks at an individual level

An Integrated Engineering-Computation Framework for Collaborative Engineering: An Application in Project Management

Today\u27s engineering applications suffer from a severe integration problem. Engineering, the entire process, consists of a myriad of individual, often complex, tasks. Most computer tools support particular tasks in engineering, but the output of one tool is different from the others\u27. Thus, the users must re-enter the relevant information in the format required by another tool. Moreover, usually in the development process of a new product/process, several teams of engineers with different backgrounds/responsibilities are involved, for example mechanical engineers, cost estimators, manufacturing engineers, quality engineers, and project manager. Engineers need a tool(s) to share technical and managerial information and to be able to instantly access the latest changes made by one member, or more, in the teams to determine right away the impacts of these changes in all disciplines (cost, time, resources, etc.). In other words, engineers need to participate in a truly collaborative environment for the achievement of a common objective, which is the completion of the product/process design project in a timely, cost effective, and optimal manner. In this thesis, a new framework that integrates the capabilities of four commercial software, Microsoft Excel™ (spreadsheet), Microsoft Project™ (project management), What\u27s Best! (an optimization add-in), and Visual Basic™ (programming language), with a state-of-the-art object-oriented database (knowledge medium), InnerCircle2000™ is being presented and applied to handle the Cost-Time Trade-Off problem in project networks. The result was a vastly superior solution over the conventional solution from the viewpoint of data handling, completeness of solution space, and in the context of a collaborative engineering-computation environment

Electronic Database Support Systems for Strategic Planning Activities in the Hospitality Industry

An electronic database support system for strategic planning activities can be built by providing conceptual and system specific information. The design and development of this type of system center around the information needs of strategy planners. Data that supply information on the organization\u27s internal and external environments must be originated, evaluated, collected, organized, managed, and analyzed. Strategy planners may use the resulting information to improve their decision making