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This paper presents an overview of decision support systems (DSSs) as applied to water management. This includes the definition of DSSs as pertinent to water management, its basic components, various techniques employed in development of DSSs, and technological and conceptual trends in DSSs. The application of DSSs in various areas of water management such as water resource management, water and wastewater treatment operations, water distribution systems, and infrastructure asset management is discussed. Calibration and validation of DSSs and future research in the development of new generations of DSSs is presented. Key words: water management, decision support system, knowledge-based systems, expert systems, decision making. Les auteurs presentent un survol des systemes de support decisionnel (SSD) tel qu'ils s'appliquent a l'amenagement de l'eau. Ceci inclut la definition des SSD selon leur pertinence pour l'amenagement de l'eau, leurs composantes de base, diverses techniques employees dans le developpement des SSD, ainsi que les tendances technologiques et conceptuelles dans les SSD. On discute de l'application des SSD dans divers domaines de l'amenagement de l'eau comme l'amenagement des ressources en eau, les operations de traitement de l'eau et des eaux usees, les systemes de distribution de l'eau, ainsi que l'amenagement des actifs en infrastructure. On presente la calibration et la validation des SSD et de la recherche future dans le developpement des nouvelles generations de SSD. [Traduit par la Redaction] Mots-cles: amenagement de l'eau, systeme de support decisionnel, systemes bases sur la connaissance, systemes experts, prise de decision., 1. Introduction Management of water is a complex engineering problem that encompasses various technical, economic, social, cultural, environmental, and legal issues (Global Water Partnership 2013) and depends on various forms [...]

Reducing the cost of operations is one of the most important considerations for urban transport systems. Deadhead kilometer costs are an important aspect of operating costs and are associated with buses traveling empty to and from depots; minimizing these costs is referred to as the bus-to-depot allocation problem and addressing it may be important in reducing overall costs. We present a model and an associated decision support system (DSS) for optimally allocating buses to depots while minimizing deadhead costs and keeping depot occupancy at 'ideal' operational levels. The model and DSS are tested in the Athens, Greece, large urban transit system and results indicate that considerable cost savings can be realized compared to current allocation schemes. DOI: 10.1061/(ASCE)TE.1943-5436.0000129 CE Database subject headings: Public transportation; Buses; Decision support systems; Greece. Author keywords: Transit, bus allocations.

Byline: Carla Roncoli (1), Christine Jost (2), Paul Kirshen (3), Moussa Sanon (4), Keith T. Ingram (5), Mark Woodin (3), Leopold Some (4), Frederic Ouattara (6), Bienvenue J. Sanfo (6), Ciriaque Sia (6), Pascal Yaka (6), Gerrit Hoogenboom (1) Abstract: This study compares responses to seasonal climate forecasts conducted by farmers of three agro-ecological zones of Burkina Faso, including some who had attended local level workshops and others who had not attended the workshops. While local inequalities and social tensions contributed to excluding some groups, about two-thirds of non-participants interviewed received the forecast from the participants or through various means deployed by the project. Interviews revealed that almost all those who received the forecasts by some mechanism (workshop or other) shared them with others. The data show that participants were more likely to understand the probabilistic aspect of the forecasts and their limitations, to use the information in making management decisions and by a wider range of responses. These differences are shown to be statistically significant. Farmers evaluated the forecasts as accurate and useful in terms of both material and non-material considerations. These findings support the hypothesis that participatory workshops can play a positive role in the provision of effective climate services to African rural producers. However, this role must be assessed in the context of local dynamics of power, which shape information flows and response options. Participation must also be understood beyond single events (such as workshops) and be grounded in sustained interaction and commitments among stakeholders. The conclusion of this study point to lessons learned and critical insights on the role of participation in climate-based decision support systems for rural African communities. Author Affiliation: (1) Department of Biological and Agricultural Engineering, The University of Georgia, Griffin, GA, 30223-1797, USA (2) Cumming School of Veterinary Medicine, International Program, Tufts University, North Grafton, MA, USA (3) Department of Civil and Environmental Engineering, Tufts University, Medford, MA, USA (4) Institut de l'Environnement et des Recherches Agricoles, Ouagadougou, Burkina Faso, West Africa (5) Southeast Climate Consortium, University of Florida, Gainesville, FL, USA (6) Direction de la Meteorologie, Ouagadougou, Burkina Faso, West Africa Article History: Registration Date: 05/06/2008 Received Date: 19/06/2007 Accepted Date: 07/05/2008 Online Date: 18/07/2008

ABSTRACT A web-based decision support system (DSS) can provide management with a strategic plan for business process reengineering (BPR) in a health-care system. An attempt is made to develop a […]

In this paper, we formulate the casualty collection points (CCPs) location problem as a multi-objective model. We propose a minimax regret multi-objective (MRMO) formulation that follows the idea of the minimax regret concept in decision analysis. The proposed multi-objective model is to minimize the maximum per cent deviation of individual objectives from their best possible objective function value. This new multi-objective formulation can be used in other multi-objective models as well. Our specific CCP model consists of five objectives. A descent heuristic and a tabu search procedure are proposed for its solution. The procedure is illustrated on Orange County, California. doi: 10.1057/palgrave.jors.2602047 Published online 24 August 2005 Keywords: multi-objective; casualty collection points; facility location; heuristics

Variety of decision models have been proposed in contemporary literature to tackle the problem of screening product innovations. Although linear models have gained considerable attention and recommendation, contemporary literature contains strong evidence in support of nonlinear noncompensatory models. In this paper, the authors first demonstrate how fuzzy measures, which are defined on subsets of decision attributes, and their Choquet-integral formulation, which exhibits both compensatory and noncompensatory properties, have meaningful behavioral interpretations within the context of new-product screening. Then, they show how to address the complex problem of building such measures by applying a learning algorithm that relies on methods of judgment analysis. An accompanying case study demonstrates how organizations may customize a new product decision aid and fine tune their business strategy as actual results accrue. Finally, the authors present the results of analytical studies to compare the Choquet-integral model with other noncompensatory models, such as Martino's extended scoring model and Einhorn's conjunctive model, and heuristic approaches, such as Tversky's EBA and the lexicographic method. For the new-product-decision scenario considered in the study, the Choquet-integral model provided the best fit, measured by Pearson's rank order correlation coefficient, with all of the competing models. Index Terms--Choquet integral, decision support systems, fuzzy measure, new-product screening, noncompensatory models.

The range of multilevel issues that can be encountered in research on the use of synchronous or asynchronous group support systems is investigated. Concepts of levels of analysis from the management literature are introduced and all empirical studies of e-collaboration from seven information systems journals for the period 1999-2003 are examined.

Development of a model for a decision support system, to help firms achieve successful product/service benefit positionings, and meet consumers' expectations is discussed.

Byline: Tung Bui (1), Jerome Yen (2), Jiuru Hu (3), Siva Sankaran (4) Keywords: multi-attribute modeling; market intermediaries; market signaling; negotiation and support Abstract: Despite the rapid growth of technology and Internet-based markets, many of the current systems limit themselves to price as the single dimension variable and offer, if at all, only minimal negotiation support to the consumer. In the real world, commercial transactions take into account many other parameters both quantitative and qualitative such as product quality, speed, reputation, after sales service, etc. This paper discusses how these multiple attributes can be captured to augment standard negotiation processes in order to support electronic market transactions. Using a combination of utility theory and multicriteria decision-making, we propose heuristic algorithms to discover potential trades. In addition, the approach is included within a larger framework that incorporates market-signaling mechanisms. This not only allows for the systematic evolution of negotiation positions among buyers and sellers but can ultimately lead towards improving both market transparency and efficiency. To illustrate the multiple criteria model coupled with the dynamic market signaling framework, we report in this paper the implementation of a Web-based clearinghouse that serves the real estate market. Author Affiliation: (1) Department of Information Technology Management, University of Hawaii at Manoa, 2404 Maile Way, E303, Honolulu, Hawaii, 96822, USA (2) Department of Systems Engineering and Management, Chinese University of Hong Kong, Shatin, N.T., Hong Kong, 1160 (3) Digital Insight, Sacramento, CA, 95825, USA (4) Department of Management Information Systems, California State University, 18111 Nordhoff St., Northridge, California, 91330, USA Article History: Registration Date: 11/10/2004

The use of the analytical hierarchy process in marketing decisions is discussed.

Advanced Traveller Information Systems (ATIS) are discussed in the context of the reduction of road congestion and the improved use of the existing infrastructure. A two-step procedure will present the road user with the optimal travel routes for their journey. A dynamic route guidance system is described.

Decision support systems have become widespread in recent years. However, most of these systems are not carefully validated and this has led in some cases to serious errors. One of the principal reasons for the lack of validity is the lack of an operationalised validation methodology. A simplified validity framework has already been developed by the authors as the first part of a 3-phase approach towards devising a practical validation methodology. This paper describes the second phase, reporting as it does on a survey that has been undertaken to unearth the contingency factors that influence how the process of validation, employing the validity framework, will be carried out for a particular kind of decision support system - one involving a spreadsheet model.

Model management (MM) regards decision models as an important organisational resource deserving prudent management. Despite the remarkable volume of model management literature compiled over the past twenty-odd years, very little is known about how decision makers actually benefit from employing model management systems (MMS). In this paper, we report findings from an experiment designed to verify the idea that the adequacy of modeling support provided by a MMS influences the decision maker's problem solving performance and behaviour. We show that the decision makers who receive adequate modelling support from MMS outperform those without such support. Also, we provide empirical evidence that the MMS help turn the decision makers' perception of problem solving from a number crunching task into development of solution strategies, consequently changing their decision making behaviour.

The role of assumptions in decision making models based on metagraphs was investigated. An analytical approach was proposed to represent assumptions about the validity of decision model bases, examine assumptions that are necessary for solving a particular problem using a given decision model and determine how the problem specification or the context can be modified to make that problem solvable. Results showed that metagraphs can be extended to include assumption use and representation. Metagraphs, for instance, can be drawn pictorially for problems involving small model bases. Thus, metagraph-based model bases can actively support important model management functions such as model evaluation and selection. It was also found that projections and contexts of decision model bases consisting of assumptions are commutative.

Introduction Big Bend Groundwater Management District No. 5 (GMD5) is a major agricultural region in central Kansas. The predominant source of fresh water is the Great Bend Prairie (GBP) alluvial [...]

To operate strategically, corporate decision-makers need to assess functional-level projects based upon their ability to fulfill higher-level strategic business objectives. To support such decision-making, a model framework is developed that first aggregates expected project performance across individual business activities using an additive value function and, second, across the strategic objectives of the business using a displaced ideal approach. The two-dimensional (2-D) model can be applied iteratively in a define-analyze-refine cycle that highlights how proposed functional-level projects can be enhanced to better fulfill business-level strategic objectives. To deal with the imprecision introduced due to the strategic infrequent decision situations in which the model is used, the user inputs are defined as, and the model is developed using, fuzzy numbers. Operationalized as a computer-based decision support system, the model has been successfully applied at four electronics manufacturers.

As a part of a substation-level decision support system, a new intelligent Hierarchical Fault Diagnosis System for on-line fault diagnosis is presented in this paper. The proposed diagnosis system divides the fault diagnosis process into two phases. Using time-stamped information of relays and breakers, phase I identifies the possible fault sections through the Group Method of Data Handling (GMDH) networks, and phase II recognizes the types and detailed situations of the faults identified in phase I by using a fast bit-operation logical inference mechanism. The diagnosis system has been practically verified by testing on a typical Taiwan power secondary transmission system. Test results show that rapid and accurate diagnosis can be obtained with flexibility and portability for fault diagnosis purpose of diverse substations. Keywords: Fault Diagnosis, Transmission & Distribution (T&D) System, Group Method of Data Handling, Object-Oriented Programming

In many developed countries, today's socioeconomic environment has expanded the role of the technical manager. Organizations capable of recruiting technical managers with adequate management education and interpersonal skills, in addition to technical expertise, are more likely to be successful in managing their limited resources. A technical manager's success is also dependent on the manager's acceptance by his/her subordinates, peers, and superiors, and the decision to hire a technical manager should be made with their participation. Many of these individuals have little background or experience in hiring, and they need appropriate decision support. This paper presents a framework to help a group of decision makers define and articulate a hierarchy of hiring criteria and subcriteria and rate each of the candidates on that hierarchy. To improve consistency among group members, the proposed group decision support system (GDSS) combines the Analytic Hierarchy Process (AHP) with the Delphi principles of anonymous feedback and iteration. Given the decision makers' desire for a consensus choice, the framework deviates from the normal practice of AHP, and uses the Maximize Agreement Heuristic (MAH) to arrive at the final ranking of the candidates. An application to the ranking of nurse manager candidates at a hospital in the United States is presented. Key words - group decision support system, human resource selection, multicriteria decision making, Analytic Hierarchy Process, Maximize Agreement Heuristic, Delphi

This paper discusses model based reasoning applied to protection system performance analysis. Appropriate modelling and reasoning methodologies are indicated, and their advantages considered. The necessity of incorporating protection system performance analysis within a decision support system (DSS), designed for utility protection engineers, is presented. Alarm processing and fault diagnosis are demonstrated as further requirements of the DSS for protection engineers, within which knowledge based reasoning and model based reasoning are combined to provide the overall functionality required.

A computational cased-based reasoning model that supports ill-structured oriented classification decisions is developed. It is shown that the model can handle quantitative, qualitative, logic and nominal decision variables and can solve classification decision problems by inferencing syntactic patterns in a database of past cases. However, the model is not applicable to environments that require real-time control.

This paper presents a modeling technique that extracts judgments and decisions from experts to derive a consensual model for decision support. The proposed approach is applied to build a decision support system for the new product entry timing decision. Experience learned from the proposed methodology suggests that it is possible to (i) capture consensual knowledge from a group of experts, (ii) model simultaneous relationships among interacting factors, and (iii) offer a robust decision support tool.

Several decision support tools for managing credit risk associated with home mortgage portfolios are introduced. These include a forecasting model of mortgage life based on Markov chains and nonstationary transition probabilities as well as logistic and regression models for determining losses from bad loans. These models enable financial institutions to characterize the performance of mortgages and portfolio segments under various business conditions.

A contingent claims valuation model for determining the optimal budget for volume flexible equipment is proposed. The model, which assumes a stochastic demand, correlates the operations and financial aspects of capital allocation decisions by quantitatively linking productivity, volume flexibility, managerial control over output, and the firm's market value as decision variables. It is based on the concept that volume flexibility results in lower costs, more sales and better customer service.

A simplified version of a decision support system was developed for managing Health Net's fixed-income portfolios worth $370 million and for analyzing 36 different types of fixed-income securities and derivatives for risk and return. Object-oriented programming was used to integrate mathematical models and database system. This was done by uniformly implementing mathematical models for interest rate movements and cash flows of securities, database entities and the interface as interacting objects.

Our research goal is to develop and validate an expert system that screens innovations prior to commercialization. This is an important research issue because business corporations are highly dependent on innovations for their growth and profitability, yet most corporations suffer from a high rate of new product failure. Few of the existing decision support systems have alleviated this problem, partly because of their inability to deal with nonmathematical (logical) relationships. An expert system for new product planning could save organizations tremendous amounts of resources (such as dollars, time and scientific talent) spent on product failures. The design of the proposed knowledge-based system is built upon our earlier work in this area [20]-[22]. We have addressed several critical research issues in the development of such a system: choice of the appropriate sources of knowledge, resolution of conflict among human experts chosen for knowledge acquisition, use of knowledge programming techniques that can accommodate uncertainty, and multiple methods of system validation. The research makes several contributions to marketing theory and practice. Most notably, the development of such systems contributes to effective product planning in organizations and enhances resource efficiency. Further, it generates guidelines for capturing and using expertise in highly unstructured decision-making situations such as product management.

Software maintenance is a challenging activity made more complex by pressures for immediate fixes in an environment of limited resources. To commit these resources in an optimal fashion, it is necessary to adopt a long-term perspective. This paper provides a framework that facilitates selection of software maintenance projects and their staffing. Variables involved in the modeling process include project utility, project cost; maintenance budgets, staff supply and scheduling factors. An integer programming model is used to identify a subset of projects to be undertaken together with a multi-period schedule of when to accomplish the work. Finally a procedure based on the transportation algorithm assigns staff to the various selected projects. The need to incorporate judgement and address nonquantifiable factors coupled with uncertainty regarding the values for several of the variables dictates that the process be repeated multiple times to generate solutions which are disparate, several of which could well be statisficing. The methodology forces a long-term perspective for maintenance and provides a structure for what could be a very ad hoc process. The overall focus of the model presented is that of a decision aid in that it interacts with the decision maker in support of the decision.

The coordination problems that arise in decision support groups such as sharing of databases, model bases and reporting tools, are examined and the job concept is employed for modelling multi-user processes in decision-support projects. Conceptual design, empirical development and actual application of the system that supports model-based reasoning and helps in the coordination of multi-user work-flow processes are presented.

A decision support system which was designed based on a statistical model for the prediction of resource availability is a useful approach in admission planning for hospital decision makers. Admission planning pertains to the selection of elective patients from a waiting list to achieve optimal utilization of available beds, nursing staff and operating room facilities while considering emergency admissions. Three different hospital situations were used to test the approach, from which sufficiently accurate results were obtained.

This study applies factor analysis of an author cocitation frequency matrix derived from a database file consisting of a total of 15,030 cited reference records taken from 692 citing articles. Seven informal clusters of decision support systems (DSS) research subspecialties and reference disciplines were uncovered. Four of them represent DSS research subspecialties - foundations, group DSS, model/data management, and individual differences. Three other conceptual groupings define the reference disciplines of DSS - organizational science, multiple criteria decision making, and artificial intelligence. DSS is a very young academic field and is still growing. DSS has just entered the era of growth after 20 years of research. During the 1990s, DSS research will be further grounded in a diverse set of reference disciplines. Furthermore, DSS is in the active process of solidifying its domain and demarcating its reference disciplines. A DSS theory is imminent in the very near future in some area of DSS research such as model management. Key words - decision support systems, reference disciplines, bibliometrics, bibliography, cocitation analysis

A decision support model for the planning and assessment of government export promotion programs is presented. The model contains a total of four consecutive filters which are based on selection and decision rules. The model is demonstrated using data from Belgium. The results show that the model can be used as an effective decision support tool although it has shortcomings in terms of a high level of data aggregation.

The use of a decision support system (DSS) for the development of the examination problem is analyzed. The problem assumes that examination plans are based on appropriateness, correct answer rate, rate deviation and necessary time. In addition, the teacher selects the best compromise plan based on content, form and question balance. It is shown that the DSS contributed to examination problem composition.

The application of an algorithm for message routing in a hierarchical communication network is analyzed. The network under study carries two levels where messages are communicated through network node pairs. The first level network features capacitated arcs, while the other level represents a spanning tree. It is shown that a time algorithm defined as O(n2 + nw) solves the network's decision problem involving communication breakdown.

A multiple criteria decision support system is developed for evaluating strategic alternatives. The strategic assessment model incorporates the objective information and subjective judgment of the expert. Decision-making is also aided by the breakdown of environmental factors into components used with the analytic hierarchy process, subjective probabilities, entropy concept and utility theory. An application of the model is discussed.

A new graph-theoretic structure known as metagraph can be used in the formulation and application of decision support systems (DSS). Unlike other tools for DSS development, a metagraph can serve as a useful and extensive basis for designing all DSS components or for solving issues regarding DSS analysis and design. It allows the incorporation of features that are not sufficiently captured by other structures, such as diagraphs and hypergraphs. For instance, a metagraph has new properties that involve paths and connectivity, giving an analytical framework that is much more useful than diagraphs and hypergraphs. System designers and users can use metagraphs in such activities as module manipulation, data management and system integration.

A decentralized decision support system for forest management with a central coordination tool is formulated. Comprised of a linear programming model, a forest estate simulation model, a geographic information system and a provincewide central coordination device, each of its components can be used separately. However, their linkages allow the handling of the complex network of integration between subsystems and the global system of the forest resource.

In this paper we present an extension to the traditional compromise Decision Support Problem (DSP) formulation. In this formulation we use Bayesian statistics to model uncertainties associated with the information being used. In an earlier paper we have introduced a compromise DSP that accounts for uncertainty using fuzzy set theory. In this paper we describe the Bayesian Decision Support Problem. We use this formulation to design a portal frame structure. We discuss the results and compare them with those obtained using the fuzzy DSP. Finally, we discuss the efficacy of incorporating Bayesian statistics into the traditional compromise DSP formulation and describe some of the pending research issues.

Logistics managers can best cope with the complexities and uncertainties brought about by increased globalization of business activities by using an integrated decision support system (DSS) that connects worldwide communication and distribution networks among the parent company, its foreign partners and third-party logistics personnel. Such an integrated DSS will help the multinational company to better control and coordinate international transactions.