Decision making in fuzzy environment and multicriteria power engineering problems

This paper presents results of research into the use of the Bellman-Zadeh approach to decision making in a fuzzy environment for solving multicriteria power engineering problems. The application of the approach conforms to the principle of guaranteed result and provides constructive lines in computationally effective obtaining harmonious solutions on the basis of solving associated maxmin problems. The presented results are universally applicable and are already being used to solve diverse classes of power engineering problems. It is illustrated by considering problems of power and energy shortage allocation, power system operation, optimization of network configuration in distribution systems, and energetically effective voltage control in distribution systems. (c) 2011 Elsevier Ltd. All rights reserved.

Playing Second Fiddle: Expert Advice and Decision-Making in Switzerland

This thesis concerns the role of scientific expertise in the decision-making process at the Swiss federal level of government. It aims to understand how institutional and issue-specific factors influence three things: the distribution of access to scientific expertise, its valuation by participants in policy for- mulation, and the consequence(s) its mobilization has on policy politics and design. The theoretical framework developed builds on the assumption that scientific expertise is a strategic resource. In order to effectively mobilize this resource, actors require financial and organizational resources, as well as the conviction that it can advance their instrumental interests within a particular action situation. Institutions of the political system allocate these financial and organizational resources, influence the supply of scientific expertise, and help shape the venue of its deployment. Issue structures, in turn, condition both interaction configurations and the way in which these are anticipated by actors. This affects the perceived utility of expertise mobilization, mediating its consequences. The findings of this study show that the ability to access and control scientific expertise is strongly concentrated in the hands of the federal administration. Civil society actors have weak capacities to mobilize it, and the autonomy of institutionalized advisory bodies is limited. Moreover, the production of scientific expertise is undergoing a process of professionalization which strengthens the position of the federal administration as the (main) mandating agent. Despite increased political polarization and less inclu- sive decision-making, scientific expertise remains anchored in the policy subsystem, rather than being used to legitimate policy through appeals to the wider population. Finally, the structure of a policy problem matters both for expertise mobilization and for the latter's impact on the policy process, be- cause it conditions conflict structures and their anticipation. Structured problems result in a greater overlap between the principal of expertise mobilization and its intended audience, thereby increasing the chance that expertise shapes policy design. Conversely, less structured problems, especially those that involve conflicts about values and goals, reduce the impact of expertise.

Decision making in uncertain and changing environments

We consider an agent who has to repeatedly make choices in an uncertainand changing environment, who has full information of the past, who discountsfuture payoffs, but who has no prior. We provide a learning algorithm thatperforms almost as well as the best of a given finite number of experts orbenchmark strategies and does so at any point in time, provided the agentis sufficiently patient. The key is to find the appropriate degree of forgettingdistant past. Standard learning algorithms that treat recent and distant pastequally do not have the sequential epsilon optimality property.

Altered decision-making in multiple sclerosis: a sign of impaired emotional reactivity?

We assessed decision-making capacity and emotional reactivity in 20 patients with multiple sclerosis (MS) and in 16 healthy subjects using the Gambling Task (GT), a model of real-life decision making, and the skin conductance response (SCR). Demographic, neurological, affective, and cognitive parameters were analyzed in MS patients for their effect on decision-making performance. MS patients persisted longer (slope, -3.6%) than the comparison group (slope, -6.4%) in making disadvantageous choices as the GT progressed (p < 0.001), suggesting significant slower learning in MS. Patients with higher Expanded Disability Status Scale scores (EDSS >2.0) showed a different pattern of impairment in the learning process compared with patients with lower functional impairment (EDSS </=2.0). This slower learning was associated with impaired emotional reactivity (anticipatory SCR 3.9 vs 6.1 microSiemens [microS] for patients vs the comparison group, p < 0.0001; post-choice SCR 3.9 vs 6.2 microS, p < 0.0001), but not with executive dysfunction. Impaired emotional dimensions of behavior (assessed using the Dysexecutive Questionnaire, p < 0.002) also correlated with slower learning. Given the considerable consequences that impaired decision making can have on daily life, we suggest that this factor may contribute to handicap and altered quality of life secondary to MS and is dependent on emotional experience. Ann Neurol 2004.

Impact of the availability of an influenza virus rapid antigen test on diagnostic decision making in a pediatric emergency department

OBJECTIVES: Fever is one of the most commonly seen symptoms in the pediatric emergency department. The objective of this study was to observe how the rapid testing for influenza virus impacts on the management of children with fever. METHODS: We performed a review of our pediatric emergency department records during the 2008/2009 annual influenza season. The BinaxNow Influenza A+B test was performed on patients with the following criteria: age 1.0 to 16.0 years, fever greater than 38.5 °C, fever of less than 96 hours' duration after the onset of clinical illness, clinical signs compatible with acute influenza, and nontoxic appearance. Additional laboratory tests were performed at the treating physician's discretion. RESULTS: The influenza rapid antigen test was performed in 192 children. One hundred nine (57%) were influenza positive, with the largest fraction (101 patients) positive for influenza A. The age distribution did not differ between children with negative and positive test results (mean, 5.3 vs. 5.1 years, not statistically significant). A larger number of diagnostic tests were performed in the group of influenza-negative patients. Twice as many complete blood counts, C-reactive protein determinations, lumbar punctures, and urinalyses were ordered in the latter group. CONCLUSIONS: Rapid diagnosis of influenza in the pediatric emergency department affects the management of febrile children as the confirmation of influenza virus infection decreases additional diagnostic tests ordered.

Information from managing information systems as a fundamental element to support decision-making in hospitals

This article deals with the activity of defining information of hospital systems as fundamental for choosing the type of information systems to be used and also the organizational level to be supported. The use of hospital managing information systems improves the user`s decision -making process by allowing control report generation and following up the procedures made in the hospital as well.

Assisting decision-making in Queensland barley production through chance constrained programming

A chance constrained programming model is developed to assist Queensland barley growers make varietal and agronomic decisions in the face of changing product demands and volatile production conditions. Unsuitable or overlooked in many risk programming applications, the chance constrained programming approach nonetheless aptly captures the single-stage decision problem faced by barley growers of whether to plant lower-yielding but potentially higher-priced malting varieties, given a particular expectation of meeting malting grade standards. Different expectations greatly affect the optimal mix of malting and feed barley activities. The analysis highlights the suitability of chance constrained programming to this specific class of farm decision problem.

Sport-specific practice and the development of expert decision-making in team ball sports

The role of sport-specific practice in the development of decision-making expertise in the sports of field hockey, netball, and basketball was examined. Fifteen expert decision-makers and 13 experienced non-expert athletes provided detailed information about the quantity and type of sport-specific and other related practice activities they had undertaken throughout their careers. Experts accumulated more hours of sport-specific practice from age 12 years onwards than did non-experts, spending on average some 13 years and 4,000 hours on concentrated sport-specific practice before reaching international standard. A significant negative correlation existed between the number of additional activities undertaken and the hours of sportspecific training required before attaining expertise, suggesting a functional role for activities other than sport-specific training in the development of expert decision-making.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Factors influencing innovation decision making in Portuguese firms

There is an undeniable positive effect of innovation for both firms and the economy, with particular regards to the financial performance of firms. However, there is an important role of the decision making process for the allocation of resources to finance the innovation process. The aim of this paper is to understand what factors explain the decision making process in innovation activities of Portuguese firms. This is an empirical study, based on the modern theoretical approaches, which has relied on five key aspects for innovation: barriers, sources, cooperation, funding; and the decision making process. Primary data was collected through surveys to firms that have applied for innovation programmes within the Portuguese innovation agency. Univariate and multivariate statistical techniques were used. Our results suggest that the factors that mostly influence the Portuguese firms’ innovation decision-making processes are economical and financial (namely those related to profit increase and labour costs reduction).