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Abstract. In this paper, a heuristic procedure is proposed for the facility location problem with general Bernoulli demands. This is a discrete facility location problem with stochastic demands that can [...]

Abstract. The success of a recommender system is generally evaluated with respect to the accuracy of recommendations. However, recently diversity of recommendations has also become an important aspect in evaluating [...]

Abstract. Intcomex, a large global distributor of information technology products, was experiencing severe stress in its supply chain from a rapidly expanding set of products in its catalog. The company [...]

The eight-team Canadian Football League (CFL) features an 18-game regular season played between late June and early November. The regular-season schedule is manually created using an iterative process involving league [...]

Preparing for the annual major league baseball draft is a difficult task; with 1,500 players selected each year, teams must evaluate and rank many hundreds of potential draftees. To evaluate [...]

Managing the deteriorating bridge infrastructure has become a major social and economic concern in North America. The methodology developed in the present research consists of three methods: (1) ranking and prioritizing method to evaluate and rank all bridge projects in a network, (2) ranking method to evaluate the available rehabilitation strategies for each project, and (3) recommended work program development method. The recommended work program specifies a list of projects to allocate the available budget to and what type of action to be implemented for each project. The developed methodology allows engineers to use multiple and conflicting criteria and to incorporate their experience and judgment in the decision making process. The methodology can assist bridge engineers and decision makers in selecting the most suitable work program that can be performed with a limited budget. An example application is presented to demonstrate the use and capabilities of the developed methodology. Key words: bridge, decision, budget, rehabilitation, multi-criteria, utility, AHP. La gestion de la deterioration de l'infrastructure des ponts est devenue un enjeu economique et social majeur en Amerique du Nord. La methodologie developpee dans la recherche presentee dans cet article comporte trois methodes: (1) une methode de classement et de determination de l'ordre des priorites afin d'evaluer et de classer tous les projets de ponts dans un reseau, (2) une methode de classement pour evaluer les strategies de remise en etat disponibles pour chaque projet et (3) une methode de developpement d'un programme pour le travail recommande. Ce programme de travail recommande specifie une liste de projets afin d' allouer le budget disponible ainsi que les actions a prendre pour chaque projet. La methodologie developpee permet aux ingenieurs d' utiliser plusieurs criteres incompatibles et d' incorporer leur experience et leur jugement dans le processus de prise de decisions. Cette methodologie peut aider les ingenieurs de ponts et les decideurs a choisir le meilleur programme de travail qui peut etre realise a l'interieur d'un budget limite. Un exemple demontre l'utilisation et les capacites de la methodologie developpee. Mots-cles : pont, decision, budget, remise en etat, multicriteres, utilite, MHM. [Traduit par la Redaction], Introduction Reports on the status of civil infrastructure in North America demonstrate that the deteriorating bridge infrastructure requires immediate attention. In the 2009 report card for America's infrastructure, the American [...]

Byline: Victor E. Cabrera (1), Norman E. Breuer (2), Peter E. Hildebrand (3) Abstract: Dairy farmers face increasing pressure to decrease environmental impact while remaining economically viable. Adaptation of farm management practices in response to seasonal climate forecasts may be one means of achieving these objectives. This paper describes the interactive and iterative process by which farmers, researchers, extension agents, regulatory agencies, and other stakeholders collaborated to create, calibrate, and validate the Dynamic North Florida Dairy Farm model (DyNoFlo), a whole-farm decision support system to decrease nitrogen leaching while maintaining profitability under variable climate conditions. Participatory modeling may enhance the creation of adoptable and adaptable user-friendly models that include environmental, economic and biophysical components. By providing farmers, policy makers, and other stakeholders with a more holistic view of current practices, common ground among them was more easily identified and collaboration was fostered. Farmer values included willingness to be good environmental stewards when they are profitable. The participatory research and development process enhanced understanding of and potential adaptation to seasonal climate variability conditioned to the El Nino Southern Oscillation (ENSO) phases in light of increasing environmental regulations and economic challenges. Adoption of the collaboratively-developed DyNoFlo is expected to be higher than usual because stakeholders feel greater ownership of the final product. Author Affiliation: (1) Agricultural Science Center at Clovis, New Mexico State University, 2346 SR 288, Clovis, NM, 88101-9998, USA (2) Rosenstiel School of Marine and Atmospheric Science, University of Miami, 256 Frazier Rogers Hall, P.O. Box 110570, Gainesville, FL, 32611, USA (3) Food and Resource Economic Department, University of Florida, 1172 McCarty Hall, P.O. Box 110240, Gainesville, FL, 32611-0240, USA Article History: Registration Date: 21/11/2007 Received Date: 10/12/2006 Accepted Date: 06/11/2007 Online Date: 22/12/2007

A study was conducted to evaluate the effect of case-based reasoning (CBR) as an input to judgment. A psychological theory on the use of CBR and its attenuation of biases is developed. Findings indicate that participants who were shown CBR cases made judgments closer to regression advice than those who were only shown regression advice.

Byline: Carolina A. M. Schurink (1), Stefan Visscher (1), Peter J. F. Lucas (2), Henk J. Leeuwen (1,3), Erik Buskens (4), Reinier G. Hoff (5), Andy I. M. Hoepelman (1,3), Marc J. M. Bonten (1,3,4) Keywords: Ventilator-associated pneumonia; Decision-support system; Bayesian network Abstract: Objective To determine the diagnostic performance of a Bayesian Decision-Support System (BDSS) for ventilator-associated pneumonia (VAP). Design A previously developed BDSS, automatically obtaining patient data from patient information systems, provides likelihood predictions of VAP. In a prospectively studied cohort of 872 ICU patients, VAP was diagnosed by two infectious-disease specialists using a decision tree (reference diagnosis). After internal validation daily BDSS predictions were compared with the reference diagnosis. For data analysis two approaches were pursued: using BDSS predictions (a) for all 9422 patient days, and (b) only for the 238a-days with presumed respiratory tract infections (RTI) according to the responsible physicians. Measurements and results 157 (66%) of 238a-days with presumed RTI fulfilled criteria for VAP. In approach (a), median daily BDSS likelihood predictions for days with and without VAP were 77% [Interquartile range (IQR)a-=a-56--91%] and 14% [IQR 5--42%, pa- Conclusions As compared with the reference diagnosis, the BDSS had good test characteristics for diagnosing VAP, and might become a useful tool for assisting ICU physicians, both for routinely daily assessment and in patients clinically suspected of having VAP. Empirical validation of its performance is now warranted. Author Affiliation: (1) Division of Internal Medicine, Geriatrics and Infectious Diseases, University Medical Center Utrecht, Heidelberglaan 100, HP F.02.126, 3584 CX, Utrecht, The Netherlands (2) Institute for Computing and Information Sciences, Radboud University, Nijmegen, The Netherlands (3) Eijkman-Winkler Laboratory for Microbiology, University Medical Center Utrecht, Heidelberglaan 100, HP F.02.126, 3584 CX, Utrecht, The Netherlands (4) Julius Center for Health Sciences and Primary Health Care, University Medical Center Utrecht, Heidelberglaan 100, HP F.02.126, 3584 CX, Utrecht, The Netherlands (5) Division of Perioperative and Emergency Care, University Medical Center Utrecht, Heidelberglaan 100, HP F.02.126, 3584 CX, Utrecht, The Netherlands Article History: Registration Date: 09/05/2007 Received Date: 10/11/2006 Accepted Date: 08/05/2007 Online Date: 16/06/2007 Article note: Electronic supplementary material The online version of this article (doi: 10.1007/s00134-007-0728-6) contains supplementary material, which is available to authorized users.

A study is conducted to examine the dissimilarities among a group of milti-criteria decision support systems.

This paper develops an integrated neural-networkbased decision support system for predictive maintenance of rotational equipment. The integrated system is platform-independent and is aimed at minimizing expected cost per unit operational time. The proposed system consists of three components. The first component develops a vibration-based degradation database through condition monitoring of rolling element bearings. In the second component, an artificial neural network model is developed to estimate the life percentile and failure times of roller bearings. This is then used to construct a marginal distribution. The third component consists of the construction of a cost matrix and probabilistic replacement model that optimizes the expected cost per unit time. Furthermore, the integrated system consists of a heuristic managerial decision rule for different scenarios of predictive and corrective cost compositions. Finally, the proposed system can be applied in various industries and different kinds of equipment that possess well-defined degradation characteristics. Index Terms--Cost-optimal control, decision support systems, maintenance, neural network applications.

The focus of this paper centers on the condition assessment of 11-kV-33-kV distribution circuit breakers (CBs) from the analysis of their trip coil current signatures captured using an innovative condition monitoring technology developed by others. Using available expert knowledge in conjunction with a structured process of data mining, thresholds associated with features representing each stage of a CB's operation may be defined and used to characterize varying states of the CB condition. The knowledge and understanding of the satisfactory and unsatisfactory breaker condition can be gained and made explicit from the analysis of captured trip signature data and subsequently used to form the basis of condition assessment and diagnostic rules implemented in a decision support system, used to inform condition-based decisions affecting CB maintenance. This paper proposes a data mining method for the analysis of condition monitoring data, and demonstrates this method in its discovery of useful knowledge from trip coil data captured from a population of Scottish Power-Energy Networks' in-service CBs. This knowledge then forms the basis of a decision support system for the condition assessment of these CBs during routine trip testing. Index Terms--Circuit breakers (CBs), condition-based maintenance, data mining, decision support system, monitoring, trip coil current signature.

The key to a successful implementation of a build-operate-transfer (BOT) infrastructure project is in-depth analysis of all aspects related to economic, environmental, social, political, legal, and financial feasibility of the project. For these reasons, the analysis of the project feasibility decision needs a technique to include the qualitative decision factors that have a strong impact on the project. This paper aims to introduce a decomposed evaluation model developed to assess the most common significant decision factors that strongly affect the feasibility of BOT projects. The paper describes the viability decision factors that were identified and screened with the assistance of a group of industry experts. This analysis yielded 21 significant factors that would have a certain impact on the feasibility of any BOT project. These factors were classified into three relative categories forming the structure of the suggested project viability model. This model presents a new approach, based on the analytical hierarchy process technique, to evaluate the relationships between decision factors related to project feasibility determination. The new approach has been validated by information obtained from three case studies of BOT projects. The proposed approach to project feasibility evaluation aims to increase the decision maker's ability to determine the factors contributing the most to the viability to the BOT project at hand. DOI: 10.1061/(ASCE)0733-9364(2007)133:1(50) CE Database subject headings: Build/operate/transfer; Infrastructure; Decision support systems; Construction management.

Methods for defuzzification of fuzzy sets in decision support systems are presented.

The formulation of an appropriate contract strategy is a fundamental yet critical aspect of contractual arrangement for a project. This paper presents a decision support system (DSS) prototype for contract strategy formulation using the case-based reasoning (CBR) approach. The prototype is called CB-Contract. An overview on the scope and formulation process of contract strategy is provided. Contract strategy is regarded as comprising four main substrategies: (1) work packaging; (2) functional grouping; (3) contract type; and (4) award method. The significance of CBR in contract strategy formulation is examined. The overall architecture of CB-Contract is discussed, with particular emphasis on its knowledge component. A case structure for case representation has been suggested taking into account the important factors that need to be considered while formulating a contract strategy, in particular project characteristics, client's objectives, and client's comparative advantages. Issues pertaining to case indexing and similarity calculation for efficient retrieval of similar cases are explored. An illustrative example to obtain similar cases for a given set of project information is presented. Case adaptation that considers the robustness of each substrategy, the compatibility of the substrategies, and the expected effectiveness of the contract strategy is also included in the illustrative example. DOI: 10.1061/(ASCE)0887-3801(2006)20:5(339) CE Database subject headings: Contracts; Decision support systems; Construction management.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.apergo.2006.04.021 Byline: Dick Lenior (a), Wiel Janssen (b), Mark Neerincx (c), Kirsten Schreibers (a) Keywords: Traffic control; Decision support; Supervision; Adaptive systems; Cognitive engineering Abstract: The theme Smart Transport can be described as adequate human-system symbiosis to realize effective, efficient and human-friendly transport of goods and information. This paper addresses how to attune automation to human (cognitive) capacities (e.g. to take care of information uncertainty, operator trust and mutual man-machine adaptations). An introduction to smart transport is presented, including examples of best practice for engineering human factors in the vehicle ergonomics and train traffic control domain. The examples are representative of an ongoing trend in automation and they show how the human role changes from controller to supervisor. Section 2 focuses on the car driver and systems that support, or sometimes even take over, critical parts of the driving task. Due to the diversity of driver ability, driving context and dependence between driver and context factors, there is a need for personalised, adaptive and integrated support. Systematic research is needed to establish sound systems. Section 3 focuses on the train dispatcher support systems that predict train movements, detect potential conflicts and show the dispatcher the possibilities available to solve the detected problems. Via thorough analysis of both the process to be controlled and the dispatcher's tasks and cognitive needs, support functions were developed as part of an already very complex supervision and control system. The two examples, although from a different field, both show the need for further development in cognitive modelling as well as for the value of sound ergonomics task analysis in design practice. Author Affiliation: (a) ErgoS Engineering and Ergonomics, PO Box 267, Enschede, The Netherlands (b) TNO HF, PO Box 23, Soesterberg, The Netherlands (c) Delft University of Technology/TNO HF, PO Box 23, Soesterberg, The Netherlands Article Note: (footnote) [star] This paper covers the two keynotes in the symposium 'Ergonomics on the move -- Smart Transport', an integral part of the IEA2006 conference, by Wiel Janssen -- section 2 and Dick Lenior -- section 3.

This paper reports on the use of multi-agent system technology to automate the management and analysis of SCADA and digital fault recorder (DFR) data. The multi-agent system, entitled Protection Engineering Diagnostic Agents (PEDA), integrates legacy intelligent systems that analyze SCADA and DFR data to provide data management and online diagnostic information to protection engineers. Since November 2004, PEDA agents have been intelligently interpreting and managing data online at a transmission system operator in the U.K. As the results presented in this paper demonstrate, PEDA supports protection engineers by providing access to interpreted power systems data via the corporate intranet within minutes of the data being received. In this paper, the authors discuss their experience of developing a multi-agent system that is robust enough for continual online use within the power industry. The use of existing agent development toolsets and standards is also discussed. Index Terms--Cooperative systems, decision support systems, fault diagnosis, intelligent systems, knowledge-based systems, power transmission protection.

Online diagnostics and online condition monitoring are important functions within the operation and maintenance of a power plant. When there is knowledge of the relationships between the raw data and the underlying phenomena within the plant item, typical intelligent system-based interpretation algorithms can be implemented. Increasingly, health data is captured without any underlying knowledge concerning the link between the data and their relationship to physical and electrical phenomena within the plant item. This leads to the requirement for dynamic and learning condition monitoring systems that are able to determine the expected and normal plant behavior over time. This paper describes how multi-agent system technology can be used as the underpinning platform for such condition monitoring systems. This is demonstrated through a prototype multi-agent anomaly detection system applied to a 2.5-MW diesel engine driven alternator system. Index Terms--Cooperative systems, decision support systems, generators, intelligent systems, monitoring, multi-agent systems.

The use of advanced decision support system (DSS) capabilities is hampered by the inadequacy of a "toolbox" organization of DSS from the user's perspective. In such a setup, the user is assumed to have all the knowledge and skills necessary to appropriately use the tools provided by the system in the decision-making process. This paper proposes a model for the use of autonomous agents as intermediaries between the users and the system. The model is organized around the human problem-solving process. The paper elaborates on the types of intermediary agents and the architecture for a DSS. The approach is illustrated using the prototype for an investment DSS. Index Terms--Decision support systems, human problem solving, software agents.

A study on the use of interval judgments in the simple multiattribute rating technique (SMART) and SWING weighting methods is discussed.

Abstract: The present study utilizes the principles and data provided by the Environmental Priority Strategies (EPS) methodology in order to create a multidimensional prototype, which intends to assist the damage [...]

A study is conducted to review controlled trials assessing the effects of computerized clinical decision support systems (CDSSs) and to identify study characteristics predicting its benefit. The study concluded that many CDSSs improve practitioner performance and that the effects on patient outcomes, when studied, were inconsistent.

The Decision Support Systems (DCS) that are presently in vogue are rigid knowledge-based systems. The problems of reducing the space occupied by decision tables constructed for real applications are examined.

The design-build procurement route is gaining popularity and being extensively used by many clients. Scrutinizing the capabilities of design-build 'candidate' organizations (who submit proposals for prequalification/short listing), is a complex task that demands the evaluation of several quantitative and qualitative attributes. The crucial task of design-builder prequalification needs multidisciplinary expertise that often poses tough challenges to many construction clients. A Hong Kong based cross-sectional research study of various international clients' design-builder selection approaches unveiled several selection strategies and criteria used: and benchmarked some best practices. Based on such consolidated knowledge, a structured design-builder selection model was developed. The conceptualized frameworks for design-builder prequalification are described in this paper. An overview of the development and preliminary validation of a prototype web-based decision support system for design-builder prequalification is also presented in this paper. CE Database subject headings: Design/build; Contractors; Internet: Decision support systems: Construction industry.

We present a new approach for adaptive presentation of structured information, based on preference-based constrained optimization techniques rooted in qualitative decision-theory. In this approach, document presentation is viewed as a configuration problem whose goal is to determine the optimal presentation of a document, while taking into account the preferences of the content provider, viewer interaction with the browser, and, possibly, some layout constraints. The preferences of the content provider are represented by a CP-net, a graphical, qualitative preference model developed in Boutilier et al. [1999]. The layout constraints are represented as geometric constraints, integrated within the optimization process. We discuss the theoretical basis of our approach, as well as implemented prototype systems for Web pages and for general media-rich document presentation. Categories and Subject Descriptors: D.2.2 [Software Engineering]: Design Tools and Techniques--User interfaces; H.4.2 [Information Systems Applications]: Types of Systems--Decision support (e.g., MIS); H.4.3 [Information Systems Applications]: Communications Applications--Information browsers; H.5.2 [Information Interfaces and Presentation (e.g., NCI)]: User Interfaces--Interaction styles (e.g., commands, menus, forms, direct manipulation); user interface management systems (UIMS); H.5.4 [Information Interfaces and Presentation]: Hypertext/Hypermedia--Navigation; I.2.4 [Artificial Intelligence]: Knowledge Representation Formalisms and Methods--Representations (procedural and rule-based)

This paper describes an investigation into the influence of contingency factors on the validation of spreadsheet-based decision support systems (DSS), and develops a methodological framework for validation that takes account of the effect of contingency factors. The research extends and confirms previous research by one of the authors who identified relevant contingency factors. The perceived influence of these contingency factors on validation effort was investigated by an empirical study, and the results of this study were then used to derive contingency-related guidance for validation. This was evaluated by a sample of practitioners and academics with experience in the development of spreadsheet-based DSS, and was then incorporated into a methodological framework for validation. The framework is designed to enable managers, decision-makers, project leaders and other non-OR specialists to identify the extent of validation effort likely to be required to ensure that the spreadsheet models that they build are valid. The research has implications for the validation of other types of OR models. Keywords: contingency factors; decision support; modelling; spreadsheet; validation

Byline: Richard G. Brody (1), Tamara K. Kowalczyk (2), John M. Coulter (3) Keywords: decision aids; knowledge acquisition; declarative knowledge Abstract: This study provides evidence on how the use of a computerized decision aid affects knowledge acquisition. While the intent of such computer-based decision aids is to improve and support unaided human judgments, it is unclear whether the use of the aids actually facilitate knowledge transfer. Seventy-six subjects completed a hypothetical decision task where one of two types of decision aids was used: an expert system or traditional textual materials. Results suggest that those using a computer-based decision aid acquired and encoded in memory less declarative knowledge than those using textual reference materials. Implications of the findings are discussed. Author Affiliation: (1) University of New Haven, USA (2) Department of Accounting, College of Business and Economics, Western Washington University, Bellingham, WA, 98225-9071 (3) Western New England College, England Article History: Registration Date: 05/10/2004

A research on the effects of Decision Support System (DSS) on strategic decision making is done. DSS has been in use for more than 30 years and it focuses on the system variables only.

As long as 150 years ago, when Fritz and Hitzig demonstrated the electrical excitability of the motor cortex, scientists and fiction writers were considering the possibility of interfacing a machine with the human brain. Modern attempts have been driven by concrete technological and clinical goals. The most advanced of these has brought the perception of sound to thousands of deaf individuals by means of electrodes implanted in the cochlea. Similar attempts are underway to provide images to the visual cortex and to allow the brains of paralyzed patients to re-establish control of the external environment via recording electrodes. This review focuses on two challenges: (1) establishing a 'closed loop' between sensory input and motor output and (2) controlling neural plasticity to achieve the desired behavior of the brain-machine system. Meeting these challenges is the key to extending the impact of the brain-machine interface.

ABSTRACT Present accounting data models such as the Resource-Event-Agent (REA) model merely focus on the modeling of static accounting phenomena. In this paper, it is argued that these models are [...]