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A new multiple decision-maker model using bi-level programming is proposed for a resource-constrained project scheduling problem in a fuzzy random environment. In the model, activity duration is assumed to be a fuzzy random variable because of the complex uncertainties in project scheduling problems. The project owner, who is the upper-level decision maker, seeks to maximize profits whereas the lower-level contractor attempts to minimize cost. A global-local-neighbor particle swarm optimization with a fuzzy random simulation is then proposed to solve the advanced model. Finally, a sub-project of Nuozhadu Hydropower Station Construction Project in China is used to illustrate an application of the developed model. A comparison with other approaches is made and the generated results validate the viability and effectiveness of the proposed model and method. Key words: resource-constrained project scheduling, multiple decision maker, bi-level programming, fuzzy random variable, particle swarm optimization. Un nouveau modele de prise de decisions multiples, utilisant une programmation a double niveau, est propose pour un probleme d'ordonnancement de projet a contrainte de personnel dans un environnement aleatoire flou. Dans le modele, la duree de l'activite est presumee etre une variable aleatoire floue en raison des incertitudes complexes dans les problemes d'ordonnancement des projets. Le proprietaire du projet, qui est le plus haut decideur, cherche a maximiser les profits, alors que l'entrepreneur de niveau inferieur cherche a minimiser les couts. Une optimisation avec essaim de particules global-local-voisin utilisant une simulation aleatoire floue est ensuite proposee pour resoudre le modele avance. Finalement, un sous-projet du projet de construction d'un barrage pour la centrale hydroelectrique Nuozhadu, en Chine, illustre une application du modele developpe. Il est compare a d'autres approches et les resultats valident la viabilite et l'efficacite du modele et de la methode proposes. [Traduit par la Redaction] Mots-cles : ordonnancement d'un projet a contrainte de personnel, modele de prise de decisions multiples, programmation a double niveau, variable aleatoire floue, optimisation par modele en banc de sable., 1. Introduction The resource-constrained project scheduling problem (RCPSP) is one of the most challenging problems in construction scheduling applications as the identification of optimal solutions are of great value to [...]

Background: Few reports have evaluated prognostic modelling studies of tools used for surgical decision-making. This systematic review aimed to describe and critically appraise studies that have developed or validated multivariable [...]

We model the decision-making process of callers in call centers as an optimal stopping problem. After each waiting period, a caller decides whether to abandon a call or continue to [...]

We study four information aggregation structures commonly used by organizations to evaluate opportunities: individual decision making, delegation to experts, majority voting, and averaging of opinions. Using a formal mathematical model, we investigate how the performance of each of these structures is contingent upon the breadth of knowledge within the firm and changes in the environment. Our model builds on work in the Carnegie tradition and in the group and behavioral decision-making literatures. We use the model to explore when delegation is preferable to other structures, such as voting and averaging. Our model shows that delegation is the most effective structure when there is diversity of expertise, when accurate delegation is possible, and when there is a good fit between the firm's knowledge and the knowledge required by the environment. Otherwise, depending on the knowledge breadth of the firm, voting or averaging may be the most effective structure. Finally, we use our model to shed light on which structures are more robust to radical environmental change and when crowd-based decision making may outperform delegation. Key words: organizational structure; decision making; knowledge; environmental change History: Received January 19, 2011; accepted December 3, 2012, by Jesper Sorensen, organizations. Published online in Articles in Advance April 4, 2013., 1. Introduction Important organizational decisions are likely to be made by groups rather than by individuals (Tindale et al. 2003, p. 381). Such groups might include top management teams, boards [...]

In many circumstances, evaluations are based on empirical data. However, some observations may be imprecise, meaning that it is not entirely clear what occurred in them. We address the question of how beliefs are formed in these situations. The individual in our model is essentially a 'frequentist' He first makes a subjective judgment about the occurrence of the event for each imprecise observation. This may be any number between zero and one. He then evaluates the event by its 'subjective' frequency of occurrence. Our model connects the method of processing imprecise observations with the individual's attitude toward ambiguity. An individual who in imprecise observations puts low (high) weight on the possibility that an event occurred is ambiguity averse (loving). An experiment supports the main assertions of the model: with precise data, subjects behave as if there were no ambiguity, whereas with imprecise data subjects turn out to be ambiguity averse. Key words: decision analysis; theory; inference; uncertainty History: Received July 7, 2010; accepted August 31, 2011, by Brad Barber, Teck Ho, and Torrance Odean, special issue editors., 1. Introduction 1.1. Motivation Let us suppose you have to undergo some medical treatment. In the first scenario you have the precise information that the treatment was successful in 25 [...]

Byline: Shyama Kuruvilla (1), Philipp Dorstewitz (2) Keywords: Public policy; Public administration; Rationality; Transactive rationality; Pragmatist philosophy; Science; Democracy; Morality; Ecological; John Dewey Abstract: The hope that policy-making is a rational process lies at the heart of policy science and democratic practice. However, what constitutes rationality is not clear. In policy deliberations, scientific, democratic, moral, and ecological concerns are often at odds. Harold Lasswell, in instituting the contemporary policy sciences, found that John Dewey's pragmatist philosophy provided an integrative foundation that took into account all these considerations. As the policy sciences developed with a predominantly empirical focus on discrete aspects of policy-making, this holistic perspective was lost for a while. Contemporary theorists are reclaiming pragmatist philosophy as a framework for public policy and administration. In this article, key postulates of pragmatist philosophy are transposed to policy science by developing a new theoretical model of transactive rationality. This model is developed in light of current policy analyses, and against the backdrop of three classical policy science theories of rationality: linear and bounded rationalism incrementalism and mixed-scanning. Transactive rationality is a 'fourth approach' that, by integrating scientific, democratic, moral, and ecological considerations, serves as a more holistic, explanatory, and normative guide for public policy and democratic practice. Author Affiliation: (1) Department of International Health, School of Public Health, Boston University, 801 Massachusetts Avenue, 3rd Floor, Boston, MA, 02118, USA (2) Department of Philosophy, Maastricht University, Grote Gracht 80-82, PO Box 616, Maastricht, The Netherlands Article History: Registration Date: 19/06/2009 Received Date: 09/03/2009 Accepted Date: 18/06/2009 Online Date: 07/07/2009

This paper presents a method for assessing the quality of a progressive design process by measuring the profitability of the product that the process generates. The proposed approach uses separations, a type of problem decomposition, to model progressive design processes. The subproblems in the separations correspond roughly to phases in the progressive design processes. The proposed method simulates the choices of a bounded rational designer for each subproblem using different search algorithms. This paper presents a simple two-variable problem to help describe the approach and then applies the approach to assess motor design processes. Different types and versions of these search processes are considered to determine if the results are robust to the decision-making model. The results indicate that well-designed progressive design processes are the best way to generate profitable product designs. Methods for assessing the quality of engineering design processes can be used to guide improvements to engineering design processes and generate more valuable products. [DOI: 10.1115/1.4001902]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.techfore.2010.01.013 Byline: Gang Xie (a), Wuyi Yue (b), Shouyang Wang (a), Kin Keung Lai (c) Keywords: Dynamic risk management; Petroleum; Variable precision rough set; Multi-objective programming Abstract: In this paper, an adaptive algorithm is designed for dynamic risk management in petroleum project investment based on a variable precision rough set (VPRS) model. In risk management, at each stage of decision-making, experts are invited to identify risk indices and support the decision-maker in evaluating the risk exposure (RE) of individual projects. The VPRS model is used to mine risk rules and determine the significance of risk indices from RE decision tables. Considering that there are multiple risks involved in any petroleum project investment, we use multi-objective programming to obtain the optimal selection of projects with minimum RE, where the significance of risk indices is assigned to each of the corresponding multi-objective functions as a weight. Moreover, we develop a risk ranking model to measure the degree of risk for individual projects in a portfolio. Finally, a numerical example based on a Chinese petroleum company's investments in overseas projects is presented to illustrate the proposed approach, and then conclusions are drawn. Author Affiliation: (a) Academy of Mathematics and Systems Science, Chinese Academy of Sciences (CAS), 55 Zhongguancun East Road, Haidian District, Beijing 100190, China (b) Department of Intelligence and Informatics, Konan University, 8-9-1 Okamoto, Kobe 658-8501, Japan (c) Department of Management Sciences, City University of Hong Kong, Hong Kong Article History: Received 30 January 2009; Revised 7 October 2009; Accepted 30 November 2009

RESEARCH ABSTRACT Increasingly, high-fidelity patient simulation (HFPS) is becoming essential to nursing education. Much remains unknown about how classroom learning is connected to student decision-making in simulation scenarios and the [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jenvman.2010.01.014 Byline: Rafael Marce (a)(b), Enrique Moreno-Ostos (b)(c), Jose Ma Garcia-Barcina (d), Joan Armengol (b) Abstract: Selection of reservoir location, the floodable basin forest handling, and the design of dam structures devoted to water supply (e.g. water outlets) constitute relevant features which strongly determine water quality and frequently demand management strategies to be adopted. Although these crucial aspects should be carefully examined during dam design before construction, currently the development of ad hoc limnological studies tailoring dam location and dam structures to the water quality characteristics expected in the future reservoir is not typical practice. In this study, we use numerical simulation to assist on the design of a new dam project in Spain with the aim of maximizing the quality of the water supplied by the future reservoir. First, we ran a well-known coupled hydrodynamic and biogeochemical dynamic numerical model (DYRESM-CAEDYM) to simulate the potential development of anoxic layers in the future reservoir. Then, we generated several scenarios corresponding to different potential hydraulic conditions and outlet configurations. Second, we built a simplified numerical model to simulate the development of the hypolimnetic oxygen content during the maturation stage after the first reservoir filling, taking into consideration the degradation of the terrestrial organic matter flooded and the adoption of different forest handling scenarios. Results are discussed in terms of reservoir design and water quality management. The combination of hypolimnetic withdrawal from two deep outlets and the removal of all the valuable terrestrial vegetal biomass before flooding resulted in the best water quality scenario. Author Affiliation: (a) Catalan Institute for Water Research (ICRA), Parc Cientific i TecnolA[sup.2]gic de la Universitat de Girona, 17003 Girona, Spain (b) Fluvial Dynamics and Hydrologic Engineering (FLUMEN), Department of Ecology, University of Barcelona, Diagonal 645, 08028 Barcelona, Spain (c) Department of Ecology and Geology, University of Malaga, Campus Universitario Teatinos, 29071 Malaga, Spain (d) Subdireccion de Desarrollo Sostenible, Consorcio de Aguas Bilbao Bizkaia, San Vicente 8, 48001 Bilbao, Spain Article History: Received 16 April 2009; Revised 19 January 2010; Accepted 28 January 2010

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2009.07.005 Byline: Kin Lam (a), Taisheng Liu (a), Wing-Keung Wong (b) Keywords: Bayesian model; Representative and conservative heuristics; Underreaction; Overreaction; Stock price; Stock return Abstract: This paper develops a model of weight assignments using a pseudo-Bayesian approach that reflects investors' behavioral biases. In this parsimonious model of investor sentiment, weights induced by investors' conservative and representative heuristics are assigned to observations of the earning shocks of stock prices. Such weight assignments enable us to provide a quantitative link between some market anomalies and investors' behavioral biases. The seriousness of an anomaly can be quantitatively assessed by investigating into its dependency on weights. New results other than the short-run underreaction and long-run overreaction can be derived and new hypotheses can be formed. Author Affiliation: (a) Department of Finance and Decision Sciences, Hong Kong Baptist University, Hong Kong (b) Department of Economics, Hong Kong Baptist University, Kowloon Tong, Hong Kong Article History: Received 26 February 2008; Accepted 1 July 2009

Contractor prequalification is basically a nonlinear two-group classification problem. A robust contractor prequalification decision model should include the ability of handling both quantitative and qualitative data. Support vector machine (SVM) is a set of related supervised learning methods which can handle data in a high dimensional feature space for nonlinear separable problems. A new contractor prequalification decision model using SVM is proposed to assist clients to identify qualified contractors for tendering in this study. A case study was used to validate the proposed decision model and the classifcation ability was compared with neural networks (NNs) and principal component analysis (PCA). The results show that the proposed SVM model outperforms NN and PCA and the merits of using SVM to mitigate the limitations of using NN are elaborated. The proposed decision model is an ideal alternative for supporting clients to perform contractor prequalification decision making. DOI: 10.1061/(ASCE)CP.1943-5487.0000030 CE Database subject headings: Contractors; Decision making; Models; Computation. Author keywords: Support vector machine; Contractor prequalification; Decision model.

This paper analyzes the decision making processes of the staff of a Mexican national marine park and how their options for natural resource management are affected by internal, external, and relational constraints. Using ethnographic data gathered from 2001-2003, I suggest that the failure of the marine park to accomplish its management goals was not from the lack of a plan to manage the marine area or from internal policies or practices, but from mismatch in objectives with other institutions of Mexican government and a consequent inability to access the needed resources and support. In addition, this paper argues for a more contextually-based understanding of decision making in organizations like protected areas that can account for many of the problems and failures that are often blamed on internal policies or practices. This paper proposes a model of 'decision spaces' that highlights the space between decision and action, in which these constraints, as well as opportunities, are confronted and potentially managed through flexible strategies that arise from the interaction between decisions and the surrounding sociocultural context. Key words: environment, decision making, marine resources, cognition

Abstract This paper presents a conceptual model of the dynamics of information seeking by public library clients in an online environment. The model is based on empirical evidence from a [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2008.12.004 Byline: Cheng-Min Feng (a), Pei-Ju Wu (a), Kai-Chieh Chia (b) Keywords: Location; Manufacturing center; Hybrid decision model; Fuzzy integral; Multiple criteria Abstract: This study presents a hybrid fuzzy integral decision-making model that integrates factor analysis, interpretive structural modeling, Markov chain, fuzzy integral and the simple additive weighted method for selecting locations of high-tech manufacturing centers in China. The analytical results of this case study demonstrate the feasibility of the proposed model for solving fuzzy multiple attribute decision-making problems, especially when criteria are interdependent. Further, the empirical study brings out some properties that are crucial for high-tech manufacturing centers to invest in China. Author Affiliation: (a) Institute of Traffic and Transportation, National Chiao Tung University, 4F, 118, Sec. 1, Chung Hsiao W. Rd., Taipei 10012, Taiwan, ROC (b) Department of Business Administration, Soo Chow University, 56, Sec. 1, Kuei-Yang Street, Taipei 10012, Taiwan, ROC Article History: Received 24 February 2006; Accepted 6 December 2008

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2009.01.054 Byline: Gilberto Montibeller (a), L. Alberto Franco (b), Ewan Lord (b), Aline Iglesias (b) Keywords: Multi-criteria decision analysis; Problem structuring; Portfolio analysis; Resource allocation decisions Abstract: Multi-criteria portfolio modelling has been extensively employed as an effective means to allocate scarce resources for investment in projects when considering costs, benefits and risks. Some of these modelling approaches allow the grouping of projects into organisational areas, thus also supporting the decision of resource allocation among organisational units in a way that is collectively efficient for the organisation. However, structuring in practice a portfolio model using this latter type of approach is not a trivial task. How should areas be defined? Where should new projects be included? How should one define the criteria to evaluate performance? As far as we know, there is very little indication in the operational research and decision sciences literatures on how to structure this type of model. This paper suggests different ways to structuring portfolio models where projects are divided into areas and evaluated by multiple criteria, and illustrates their use in two action-research projects. Drawing on these experiences it then suggests a general framework for the structuring of such models in practice. Directions for future research are also identified. Author Affiliation: (a) Department of Management, London School of Economics, Houghton Street, London WC2 2AE, UK (b) Warwick Business School, University of Warwick, UK Article History: Received 30 November 2007; Accepted 31 January 2009

Problem structuring methods (PSMs) are proposed as vital tools for coping with complex and unstructured problems that help decision-makers make decisions or come to a shared understanding of a problem situation. Despite their popularity, choosing a PSM for an unstructured problem situation is problematic as good categorization and evaluation of PSMs is lacking. As a first step we postulate a categorization of quantitative PSMs applied to multi-actor situations. We list the different application areas, the types of design that were used, and the type of outcomes the methods provide. To understand why and how certain PSMs are applied, we categorize applications of metagames/conflict analysis, hypergames, drama theory, Q-methodology, and transactional analysis. We find that method choice and validation of the applications are yet underdeveloped for this specific sub-field, and suggest further work on this as it will help to understand the added value of PSMs. doi:10.1057/jors.2008.93 Keywords: soft OR: problem structuring methods: actor analysis: stakeholder analysis

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2008.07.017 Byline: Emma Kushtina, Oleg Zaikin, PrzemysAaw RoA1/4ewski, BartAomiej MaAachowski Keywords: Education; Knowledge expansion process; Decision support systems; Cost estimation; Educational organization Abstract: The decision about curriculum modification usually takes place at the knowledge level, mainly with consideration of individual academic staff competences and qualifications. However, traditional approaches to cost estimation of curriculum modification are focused on material resources only. In this paper we present a cost estimation method and decision model for curriculum modification in educational organizations. The proposed method works at the knowledge level and employs competence sets as knowledge representation models in educational organizations. Authors used the theory of hierarchical, multilevel systems in order to define the model of the decision-making process of curriculum modification and its dimension. Basing on this and also using a fuzzy competence model the cost estimation algorithm in the form of a group competences expansion algorithm is proposed. The algorithm focuses on the cost of staff competence expansion caused by the knowledge development process. Author Affiliation: Szczecin University of Technology, Faculty of Computer Science and Information Technology, Zolnierska 49, 71-210 Szczecin, Poland Article History: Received 24 July 2006; Accepted 14 July 2008

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2008.05.003 Byline: James Moffat (a), John Medhurst (b) Keywords: Decision-making; Artificial intelligence; Simulation; Conflict Abstract: Over the past few years we have developed a number of key components which allow us to capture the effects of command decision-making in simulation models of conflict. One of these key components is the Rapid Planning process, which is based on the psychological construct of naturalistic decision-making. Validating such theoretical approaches and assumptions is an on-going activity which helps build confidence over time that our models and theories are valid within our domain of application, and can be used as the basis of sound advice to our customers in the UK Ministry of Defence. Here we present one piece of that validation; a series of command decision-making games which were analysed using a probit-based statistical approach. In the paper we show that the results of these games gives strong support to the way in which rapid planning captures such decision-making in algorithmic form. Author Affiliation: (a) Defence Science and Technology Laboratory, Farnborough, Hampshire, UK (b) Larrainzar Consulting Solutions Limited, Salisbury, Wiltshire, UK Article History: Received 20 July 2007; Accepted 5 May 2008

Recent tragedies such as Hurricane Katrina, 9/11, and the 2008 Sichuan Earthquake have revealed a need for methods to evaluate and plan for the impact of extreme events on critical infrastructure. In particular, awareness has been raised of the threat that a major disruption will lead to cascading failures that cross boundaries between interdependent infrastructure sectors, greatly magnifying human and economic impacts. To assist in planning for such extreme events, researchers are developing modeling tools to aid in making decisions about how best to protect critical infrastructures. We present some of the capabilities of this modeling approach as well as some of the challenges faced in developing such applications based on our experience with the Critical Infrastructure Protection Decision Support System (CIPDSS) model, developed for use by the Department of Homeland Security. A set of disruptions to road and telecommunication infrastructures is implemented in CIPDSS and the modeled disruptions to the original infrastructure as well as cascading effects on other infrastructure sectors are discussed. These simulations provide insights into the potential of this approach. KEY WORDS: critical infrastructure, disaster and risk management, infrastructure interdependencies, systems dynamics modeling, urban studies, Introduction In the wake of 9/11 and the devastating natural disasters of recent years, the impact of major disruptions to critical infrastructure (e.g., telecommunications, transportation, emergency services) is receiving increased [...]

Decision models under uncertainty can be used as an alternative method for assessing the embodied energy and greenhouse gas missions of different heating equipment when detailed information is not available. The method can help in the estimation of life-cycle energy use of equipment by removing obstacles in the evaluation of embodied energy. The paper presents the estimation of environmental impacts from manufacturing a noncondensing, natural gas-fired hot-water boiler with a heat capacity of about 12 kW for residential applications, in the absence of accurate data about the materials used. Results from a case study found in the literature are used for the verification of the proposed method. The embodied energy in a hot-water boiler with the heat exchanger in aluminum, for instance, is about 20,000 MJ or about 30% of the total embodied energy of a house and in the case of stainless steel, it is about 3,000 MJ or about 5%. CE Database subject headings: Decision making; Models; Environmental issues; Life cycles; Equipment.

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1540-5915.2009.00230.x Byline: Deborah E. Gibbons (1[dagger]), Subhashish Samaddar (2) Keywords: Agent-Based Models; Computational Models; Emergency Services; Health Care; Humanitarian Logistics; Interorganizational Networks; Network Structures; Public Health Systems; Referral Networks; Referral Partners; Simulation; Social Networks; and Vaccine Delivery Abstract: ABSTRACT This study uses fully factorial computer simulation to identify referral network attributes and referral decision rules that streamline the routing of people to urgent, limited services. As an example of a scenario, the model represents vaccine delivery in a city of 100,000 people during the first 30 days of a pandemic. By modeling patterns of communication among health care providers and daily routing of overflow clients to affiliated organizations, the simulations determine cumulative effects of referral network designs and decision rules on citywide delivery of available vaccines. Referral networks generally improve delivery rates when compared with random local search by clients. Increasing the health care organizations' tendencies to form referral partnerships from zero to about four partners per organization sharply increases vaccine delivery under most conditions, but further increases in partnering yield little or no gain in system performance. When making referrals, probabilistic selection among partner organizations that have any capacity to deliver vaccines is more effective than selection of the highest-capacity partner, except when tendencies to form partnerships are very low. Implications for designing health and human service referral networks and helping practitioners optimize their use of the networks are discussed. Suggestions for using simulations to model comparable systems are provided. Author Affiliation: (1)Graduate School of Business and Public Policy, Naval Postgraduate School, 555 Dyer Road, Ingersoll 333, Monterey, CA 93943, e-mail:degibbon@nps.edu (2)Robinson College of Business, Georgia State University, Atlanta, GA 30303, e-mail:s-samaddar@gsu.edu Article History: [Received: August 2007. Accepted: February 2009.] Article note: ([dagger]) Corresponding author.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jenvman.2008.11.027 Byline: Stuart Jones (a), Peter Lacey (b), Terry Walshe (a) Abstract: Lake Toolibin, an ephemeral lake in the agricultural zone of Western Australia, is under threat from secondary salinity due to land clearance throughout the catchment. The lake is extensively covered with native vegetation and is a Ramsar listed wetland, being one of the few remaining significant migratory bird habitats in the region. Currently, inflow with salinity greater than 1000 mg/L TDS is diverted from the lake in an effort to protect sensitive lakebed vegetation. However, this conservative threshold compromises the frequency and extent of lake inundation, which is essential for bird breeding. It is speculated that relaxing the threshold to 5000 mg/L may pose negligible additional risk to the condition of lakebed vegetation. To characterise the magnitude of improvement in the provision of bird breeding habitat that might be generated by relaxing the threshold, a dynamic water and salt balance model of the lake was developed and implemented using Monte Carlo simulation. Results from best estimate model inputs indicate that relaxation of the threshold increases the likelihood of satisfying habitat requirements by a factor of 9.7. A second-order Monte Carlo analysis incorporating incertitude generated plausible bounds of [2.6, 37.5] around the best estimate for the relative likelihood of satisfying habitat requirements. Parameter-specific sensitivity analyses suggest the availability of habitat is most sensitive to pan evaporation, lower than expected inflow volume, and higher than expected inflow salt concentration. The characterisation of uncertainty associated with environmental variation and incertitude allows managers to make informed risk-weighted decisions. Author Affiliation: (a) School of Botany, The University of Melbourne, VIC 3010, Australia (b) Western Australia Department of Environment and Conservation, Hough Street, Narrogin, WA 6312, Australia Article History: Received 13 March 2008; Revised 13 October 2008; Accepted 22 November 2008

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jenvman.2008.10.008 Byline: Eun-Sung Chung (a), Kil Seong Lee (b) Abstract: The objective of this study is to develop an alternative evaluation index (AEI) in order to determine the priorities of a range of alternatives using both the hydrological simulation program in FORTRAN (HSPF) and multicriteria decision making (MCDM) techniques. In order to formulate the HSPF model, sensitivity analyses of water quantity (peak discharge and total volume) and quality (BOD peak concentrations and total loads) are conducted and a number of critical parameters were selected. To achieve a more precise simulation, the study watershed is divided into four regions for calibration and verification according to landuse, location, slope, and climate data. All evaluation criteria were selected using the Driver-Pressure-State-Impact-Response (DPSIR) model, a sustainability evaluation concept. The Analytic Hierarchy Process is used to estimate the weights of the criteria and the effects of water quantity and quality were quantified by HSPF simulation. In addition, AEIs that reflected residents' preferences for management objectives are proposed in order to induce the stakeholder to participate in the decision making process. Author Affiliation: (a) Engineering Research Institute, Seoul National University, Seoul 151-741, Republic of Korea (b) Civil and Environmental Engineering, Seoul National University, Seoul 151-742, Republic of Korea Article History: Received 1 April 2008; Revised 29 September 2008; Accepted 22 October 2008

The theory of the firm under uncertainty has been traditionally studied using the expected utility approach. There are very few works done in this field of study using the risk-return approach despite the popularity of this dichotomy in the business world. This paper, therefore, applies various mean-risk models to the output decision making of a competitive firm facing uncertainty in the product price. The risk formulation used in this paper involves a pre-specified target level of profit, similar to those discussed in Fishburn (1977 and 1984). Furthermore, the measure of risk-aversion used in this model indicates the relative weight given by the agent to the risk component of the mean-risk objective function. The results of various mean-risk models are compared to those in the corresponding expected utility literature, and significant differences are found in many cases. One important difference is that whenever expected utility results require decreasing absolute risk aversion as a sufficient condition, the corresponding sufficient condition in the risk-return model of this paper is given by the condition that marginal cost is at least as large as the sum of average cost and average target level of profit. The results of this paper, in our opinion, are intuitively more appealing compared to the relatively abstract concept of decreasing absolute risk aversion., INTRODUCTION Traditionally, risk-return models have been used in portfolio theory. The theory of the firm under uncertainty has not been analyzed with the risk-return approach except for few works such [...]

The demand of resources in emergency systems often is uncertain and multiple. It has an important practical significance for research on the scheduling decision in multi-resource emergency systems. For the certain resource demand, the rich research results have achieved. The uncertain demand of single resource is discussed [7]. In this paper, for the uncertain demand of multi-resource, a weight coefficient is defined and a corresponding membership function is established for each resource by the policy-maker. A fuzzy mathematical programming model is established and an algorithm is proposed, which we find the maximum satisfactory degree of time restraint under the lowest satisfactory degree of resource demand. An example illustrates that the model is reasonable and the obtained algorithm is effective. Keywords Emergency systems, fuzzy number, satisfactory degree, scheduling decision in multi-resource, § 1. Introduction The scheduling problem of resources in emergency systems has become a hot topic. For the emergency-time is a certain number or interval number and the different type [...]

The traditional statistical approach to the evaluation of diagnostic tests, prediction models, and molecular markers is to assess their accuracy, using metrics such as sensitivity, specificity, and the receiver-operating-characteristic curve. However, there is no obvious association between accuracy and clinical value: it is unclear, for example, just how accurate a test needs to be in order for it to be considered 'accurate enough' to warrant its use in patient care. Decision analysis aims to assess the clinical value of a test by assigning weights to each possible consequence. These methods have been historically considered unattractive to the practicing biostatistician because additional data from the literature, or subjective assessments from individual patients or clinicians, are needed in order to assign weights appropriately. Decision analytic methods are available that can reduce these additional requirements. These methods can provide insight into the consequences of using a test, model, or marker in clinical practice. KEY WORDS: Decision support techniques; Outcome assessment; Prognosis.

Battered women's reasons for staying with or leaving their male partners are varied and complex. Using data from the Domestic Violence Experience in Omaha, Nebraska, a discrete-time hazard model was employed to examine a woman's decision based on four factors: financial independence, witness of parental violence, psychological factors, and the police response to the domestic violence call. Findings regarding the first three factors are consistent with previous findings. However, a negative police response did not deter a woman from leaving, which is a different finding from previous studies. Keywords: domestic violence; leaving: discrete-time hazard model

Some competitions involve teams comprising different numbers of players. For informal games, such as the popular 'pub quiz', we argue that teams with fewer players are at a disadvantage. This paper investigates the properties of these games and develops several methods for allocating handicaps within such competitions, so that the competitions may be considered fair, based on a simple Bernoulli model for correctly answering questions and assuming exchangeability of participants. We recommend a natural conjugate prior subjective handicapping rule; with this rule handicaps may be set beforehand given the judgement of the quiz setter regarding the difficulty of the questions. We also describe a posterior rule that provides improved accuracy but is calculated after the quiz is complete. Finally, the paper considers modifications of the proposed rules to cope with multiple-choice questions and progressive quizzes. Keywords: elicitation; games; probability; quizzes; subjective

Many large distributed systems can be characterized as networks where short paths exist between nearly every pair of nodes. These include social, biological, communication, and distribution networks, which often display power-law or small-world structure. A central challenge of distributed systems is directing messages to specific nodes through a sequence of decisions made by individual nodes without global knowledge of the network. We present a probabilistic analysis of this navigation problem that produces a surprisingly simple and effective method for directing messages. This method requires calculating only the product of the two measures widely used to summarize all local information. It outperforms prior approaches reported in the literature by a large margin, and it provides a formal model that may describe how humans make decisions in sociological studies intended to explore the social network as well as how they make decisions in more naturalistic settings. complex networks | search algorithms | social network analysis