Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables

KAUST Repository

Chikalov, Igor

2013-01-01

In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization of decision trees and decision rules) to conduct experiments. We show that, for each monotone Boolean function with at most five variables, there exists a totally optimal decision tree which is optimal with respect to both depth and number of nodes.

Relationships among various parameters for decision tree optimization

KAUST Repository

Hussain, Shahid

2014-01-14

In this chapter, we study, in detail, the relationships between various pairs of cost functions and between uncertainty measure and cost functions, for decision tree optimization. We provide new tools (algorithms) to compute relationship functions, as well as provide experimental results on decision tables acquired from UCI ML Repository. The algorithms presented in this paper have already been implemented and are now a part of Dagger, which is a software system for construction/optimization of decision trees and decision rules. The main results presented in this chapter deal with two types of algorithms for computing relationships; first, we discuss the case where we construct approximate decision trees and are interested in relationships between certain cost function, such as depth or number of nodes of a decision trees, and an uncertainty measure, such as misclassification error (accuracy) of decision tree. Secondly, relationships between two different cost functions are discussed, for example, the number of misclassification of a decision tree versus number of nodes in a decision trees. The results of experiments, presented in the chapter, provide further insight. © 2014 Springer International Publishing Switzerland.

Relationships among various parameters for decision tree optimization

KAUST Repository

Hussain, Shahid

2014-01-01

In this chapter, we study, in detail, the relationships between various pairs of cost functions and between uncertainty measure and cost functions, for decision tree optimization. We provide new tools (algorithms) to compute relationship functions, as well as provide experimental results on decision tables acquired from UCI ML Repository. The algorithms presented in this paper have already been implemented and are now a part of Dagger, which is a software system for construction/optimization of decision trees and decision rules. The main results presented in this chapter deal with two types of algorithms for computing relationships; first, we discuss the case where we construct approximate decision trees and are interested in relationships between certain cost function, such as depth or number of nodes of a decision trees, and an uncertainty measure, such as misclassification error (accuracy) of decision tree. Secondly, relationships between two different cost functions are discussed, for example, the number of misclassification of a decision tree versus number of nodes in a decision trees. The results of experiments, presented in the chapter, provide further insight. © 2014 Springer International Publishing Switzerland.

Totally optimal decision rules

KAUST Repository

Amin, Talha

2017-11-22

Optimality of decision rules (patterns) can be measured in many ways. One of these is referred to as length. Length signifies the number of terms in a decision rule and is optimally minimized. Another, coverage represents the width of a rule’s applicability and generality. As such, it is desirable to maximize coverage. A totally optimal decision rule is a decision rule that has the minimum possible length and the maximum possible coverage. This paper presents a method for determining the presence of totally optimal decision rules for “complete” decision tables (representations of total functions in which different variables can have domains of differing values). Depending on the cardinalities of the domains, we can either guarantee for each tuple of values of the function that totally optimal rules exist for each row of the table (as in the case of total Boolean functions where the cardinalities are equal to 2) or, for each row, we can find a tuple of values of the function for which totally optimal rules do not exist for this row.

Totally optimal decision rules

KAUST Repository

Amin, Talha M.; Moshkov, Mikhail

2017-01-01

Optimality of decision rules (patterns) can be measured in many ways. One of these is referred to as length. Length signifies the number of terms in a decision rule and is optimally minimized. Another, coverage represents the width of a rule’s applicability and generality. As such, it is desirable to maximize coverage. A totally optimal decision rule is a decision rule that has the minimum possible length and the maximum possible coverage. This paper presents a method for determining the presence of totally optimal decision rules for “complete” decision tables (representations of total functions in which different variables can have domains of differing values). Depending on the cardinalities of the domains, we can either guarantee for each tuple of values of the function that totally optimal rules exist for each row of the table (as in the case of total Boolean functions where the cardinalities are equal to 2) or, for each row, we can find a tuple of values of the function for which totally optimal rules do not exist for this row.

Westinghouse waste simulation and optimization software tool

International Nuclear Information System (INIS)

Mennicken, Kim; Aign, Jorg

2013-01-01

Applications for dynamic simulation can be found in virtually all areas of process engineering. The tangible benefits of using dynamic simulation can be seen in tighter design, smoother start-ups and optimized operation. Thus, proper implementation of dynamic simulation can deliver substantial benefits. These benefits are typically derived from improved process understanding. Simulation gives confidence in evidence based decisions and enables users to try out lots of 'what if' scenarios until one is sure that a decision is the right one. In radioactive waste treatment tasks different kinds of waste with different volumes and properties have to be treated, e.g. from NPP operation or D and D activities. Finding a commercially and technically optimized waste treatment concept is a time consuming and difficult task. The Westinghouse Waste Simulation and Optimization Software Tool will enable the user to quickly generate reliable simulation models of various process applications based on equipment modules. These modules can be built with ease and be integrated into the simulation model. This capability ensures that this tool is applicable to typical waste treatment tasks. The identified waste streams and the selected treatment methods are the basis of the simulation and optimization software. After implementing suitable equipment data into the model, process requirements and waste treatment data are fed into the simulation to finally generate primary simulation results. A sensitivity analysis of automated optimization features of the software generates the lowest possible lifecycle cost for the simulated waste stream. In combination with proven waste management equipments and integrated waste management solutions, this tool provides reliable qualitative results that lead to an effective planning and minimizes the total project planning risk of any waste management activity. It is thus the ideal tool for designing a waste treatment facility in an optimum manner

Westinghouse waste simulation and optimization software tool

Energy Technology Data Exchange (ETDEWEB)

Mennicken, Kim; Aign, Jorg [Westinghouse Electric Germany GmbH, Hamburg (Germany)

2013-07-01

Applications for dynamic simulation can be found in virtually all areas of process engineering. The tangible benefits of using dynamic simulation can be seen in tighter design, smoother start-ups and optimized operation. Thus, proper implementation of dynamic simulation can deliver substantial benefits. These benefits are typically derived from improved process understanding. Simulation gives confidence in evidence based decisions and enables users to try out lots of 'what if' scenarios until one is sure that a decision is the right one. In radioactive waste treatment tasks different kinds of waste with different volumes and properties have to be treated, e.g. from NPP operation or D and D activities. Finding a commercially and technically optimized waste treatment concept is a time consuming and difficult task. The Westinghouse Waste Simulation and Optimization Software Tool will enable the user to quickly generate reliable simulation models of various process applications based on equipment modules. These modules can be built with ease and be integrated into the simulation model. This capability ensures that this tool is applicable to typical waste treatment tasks. The identified waste streams and the selected treatment methods are the basis of the simulation and optimization software. After implementing suitable equipment data into the model, process requirements and waste treatment data are fed into the simulation to finally generate primary simulation results. A sensitivity analysis of automated optimization features of the software generates the lowest possible lifecycle cost for the simulated waste stream. In combination with proven waste management equipments and integrated waste management solutions, this tool provides reliable qualitative results that lead to an effective planning and minimizes the total project planning risk of any waste management activity. It is thus the ideal tool for designing a waste treatment facility in an optimum manner

Watershed Management Optimization Support Tool (WMOST) v2: User Manual and Case Studies

Science.gov (United States)

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that evaluates the relative cost-effectiveness of management practices at the local or watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed c...

An optimization tool for satellite equipment layout

Science.gov (United States)

Qin, Zheng; Liang, Yan-gang; Zhou, Jian-ping

2018-01-01

Selection of the satellite equipment layout with performance constraints is a complex task which can be viewed as a constrained multi-objective optimization and a multiple criteria decision making problem. The layout design of a satellite cabin involves the process of locating the required equipment in a limited space, thereby satisfying various behavioral constraints of the interior and exterior environments. The layout optimization of satellite cabin in this paper includes the C.G. offset, the moments of inertia and the space debris impact risk of the system, of which the impact risk index is developed to quantify the risk to a satellite cabin of coming into contact with space debris. In this paper an optimization tool for the integration of CAD software as well as the optimization algorithms is presented, which is developed to automatically find solutions for a three-dimensional layout of equipment in satellite. The effectiveness of the tool is also demonstrated by applying to the layout optimization of a satellite platform.

A case study of optimization in the decision process: Siting groundwater monitoring wells

International Nuclear Information System (INIS)

Cardwell, H.; Huff, D.; Douthitt, J.; Sale, M.

1993-12-01

Optimization is one of the tools available to assist decision makers in balancing multiple objectives and concerns. In a case study of the siting decision for groundwater monitoring wells, we look at the influence of the optimization models on the decisions made by the responsible groundwater specialist. This paper presents a multi-objective integer programming model for determining the location of monitoring wells associated with a groundwater pump-and-treat remediation. After presenting the initial optimization results, we analyze the actual decision and revise the model to incorporate elements of the problem that were later identified as important in the decision-making process. The results of a revised model are compared to the actual siting plans, the recommendations from the initial optimization runs, and the initial monitoring network proposed by the decision maker

Multi-stage optimization of decision and inhibitory trees for decision tables with many-valued decisions

KAUST Repository

Azad, Mohammad

2017-06-16

We study problems of optimization of decision and inhibitory trees for decision tables with many-valued decisions. As cost functions, we consider depth, average depth, number of nodes, and number of terminal/nonterminal nodes in trees. Decision tables with many-valued decisions (multi-label decision tables) are often more accurate models for real-life data sets than usual decision tables with single-valued decisions. Inhibitory trees can sometimes capture more information from decision tables than decision trees. In this paper, we create dynamic programming algorithms for multi-stage optimization of trees relative to a sequence of cost functions. We apply these algorithms to prove the existence of totally optimal (simultaneously optimal relative to a number of cost functions) decision and inhibitory trees for some modified decision tables from the UCI Machine Learning Repository.

Multi-stage optimization of decision and inhibitory trees for decision tables with many-valued decisions

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2017-01-01

We study problems of optimization of decision and inhibitory trees for decision tables with many-valued decisions. As cost functions, we consider depth, average depth, number of nodes, and number of terminal/nonterminal nodes in trees. Decision tables with many-valued decisions (multi-label decision tables) are often more accurate models for real-life data sets than usual decision tables with single-valued decisions. Inhibitory trees can sometimes capture more information from decision tables than decision trees. In this paper, we create dynamic programming algorithms for multi-stage optimization of trees relative to a sequence of cost functions. We apply these algorithms to prove the existence of totally optimal (simultaneously optimal relative to a number of cost functions) decision and inhibitory trees for some modified decision tables from the UCI Machine Learning Repository.

Integrating a Decision Management Tool with UML Modeling Tools

DEFF Research Database (Denmark)

Könemann, Patrick

by proposing potential subsequent design issues. In model-based software development, many decisions directly affect the structural and behavioral models used to describe and develop a software system and its architecture. However, these decisions are typically not connected to the models created during...... integration of formerly disconnected tools improves tool usability as well as decision maker productivity....

Development of a decision support tool for the assessment of biofuels

International Nuclear Information System (INIS)

Perimenis, Anastasios; Walimwipi, Hartley; Zinoviev, Sergey; Mueller-Langer, Franziska; Miertus, Stanislav

2011-01-01

Alternative fuels for the transport sector are gaining growing attention as a means against fossil fuel dependence and towards greener forms of energy. At the same time, however, they are surrounded with doubts concerning sustainability of their production. This work presents the basic framework for a decision support tool to evaluate biofuel production pathways, with the purpose of providing the decision maker with a structured methodology that will lead him to the final decision. The tool integrates the most important aspects along the entire value chain (i.e. from biomass production to biofuel end-use), namely the technical, economic, environmental and social aspect. The tool consists of a computational part, which can be combined with the personal preferences of the user. The analysis provides a score for the respective pathway that can be used to rank different options and select among them the optimal solution. The functionality of the tool has been tested for the case of biodiesel from rapeseed in Germany. - Research highlights: → Structure and framework of a decision support tool for the assessment of biofuels. → Inclusion of economic, environmental and social aspects along the biofuel production chain. → Development of an internal database with relevant information along the chain. → Multi-criteria analysis for the consideration of all relevant criteria. → Incorporation of personal preferences and priorities in the final result.

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

Science.gov (United States)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU

Optimal policy for value-based decision-making.

Science.gov (United States)

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-08-18

For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.

Optimization of decision rule complexity for decision tables with many-valued decisions

KAUST Repository

Azad, Mohammad

2013-10-01

We describe new heuristics to construct decision rules for decision tables with many-valued decisions from the point of view of length and coverage which are enough good. We use statistical test to find leaders among the heuristics. After that, we compare our results with optimal result obtained by dynamic programming algorithms. The average percentage of relative difference between length (coverage) of constructed and optimal rules is at most 6.89% (15.89%, respectively) for leaders which seems to be a promising result. © 2013 IEEE.

Decision and Inhibitory Rule Optimization for Decision Tables with Many-valued Decisions

KAUST Repository

Alsolami, Fawaz

2016-01-01

‘If-then’ rule sets are one of the most expressive and human-readable knowledge representations. This thesis deals with optimization and analysis of decision and inhibitory rules for decision tables with many-valued decisions. The most important

Integrated decision making for the optimal bioethanol supply chain

International Nuclear Information System (INIS)

Corsano, Gabriela; Fumero, Yanina; Montagna, Jorge M.

2014-01-01

Highlights: • Optimal allocation, design and production planning of integrated ethanol plants is considered. • Mixed Integer Programming model is presented for solving the integration problem. • Different tradeoffs can be assessed and analyzed. • The modeling framework represents an useful tool for guiding decision making. - Abstract: Bioethanol production poses different challenges that require an integrated approach. Usually previous works have focused on specific perspectives of the global problem. On the contrary, bioethanol, in particular, and biofuels, in general, requires an integrated decision making framework that takes into account the needs and concerns of the different members involved in its supply chain. In this work, a Mixed Integer Linear Programming (MILP) model for the optimal allocation, design and production planning of integrated ethanol/yeast plants is considered. The proposed formulation addresses the relations between different aspects of the bioethanol supply chain and provides an efficient tool to assess the global operation of the supply chain taking into account different points of view. The model proposed in this work simultaneously determines the structure of a three-echelon supply chain (raw material sites, production facilities and customer zones), the design of each installed plant and operational considerations through production campaigns. Yeast production is considered in order to reduce the negative environmental impact caused by bioethanol residues. Several cases are presented in order to assess the approach capabilities and to evaluate the tradeoffs among all the decisions

Understanding Optimal Decision-making in Wargaming

OpenAIRE

Nesbitt, P; Kennedy, Q; Alt, JK; Fricker, RD; Whitaker, L; Yang, J; Appleget, JA; Huston, J; Patton, S

2013-01-01

Approved for public release; distribution is unlimited. This research aims to gain insight into optimal wargaming decision-making mechanisms using neurophysiological measures by investigating whether brain activation and visual scan patterns predict attention, perception, and/or decision-making errors through human-in-the-loop wargaming simulation experiments. We investigate whether brain activity and visual scan patterns can explain optimal wargaming decision making and its devel...

Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables

KAUST Repository

Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2013-01-01

In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization

Optimization of tactical decisions: subjective and objective conditionality

Directory of Open Access Journals (Sweden)

Олег Юрійович Булулуков

2016-06-01

Full Text Available In the article «human» and «objective» factors are investigated that influencing on optimization of tactical decisions. Attention is accented on dependence of the got information about the circumstances of crime from the acceptance of correct decisions an investigator. Connection between efficiency of investigation and acceptance of optimal tactical decisions is underlined. The declared problem is not investigational in literature in a sufficient measure. Its separate aspects found the reflection in works: D. А. Solodova, S. Yu. Yakushina and others. Some questions related to optimization of investigation and making decision an investigator we discover in works: R. S. Belkin, V. А. Juravel, V. Е. Konovalova, V. L. Sinchuk, B. V. Shur, V. Yu. Shepitko. The aim of the article is determination of term «optimization», as it applies to tactical decisions in criminalistics, and also consideration of influence of human and objective factors on the acceptance of optimal decisions at investigation of crimes. In the article etymology of term is considered «optimization» and interpretation of its is given as it applies to the acceptance of tactical decisions. The types of mark human and objective factors, stipulating optimization of tactical decisions. The last assists efficiency of tactics of investigation of crimes. At consideration of «human factors» of influencing on optimization decisions, attention applies on «psychological traps» can take place at making decision. Among them such are named, as: anchoring; status quo; irreversible expenses; desired and actual; incorrect formulation; conceit; reinsurance; constancy of memory. Underlined, absence of unambiguity in the brought list over of «objective factors» influencing at choice tactical decision. The different understanding of «tactical risk» is argued, as a factor influencing on an acceptance tactical decisions. The analysis of «human» and «objective» factors influencing on

Systematic maintenance analysis with decision support method and tool for optimizing maintenance programme

International Nuclear Information System (INIS)

Laakso, K.; Simola, K.; Dorrepaal, J.; Skogberg, P.

1999-01-01

This report describes an approach to evaluate the effectiveness of test and maintenance programs of technical systems used during several years. The method combines an analysis of the historical data on faults and repairs with an analysis of the history of periodic testing and preventive maintenance action programs. The application of the maintenance analysis from the methodological point of view in the reliability centered maintenance (RCM) project for Barsebaeck nuclear power plant is described. In order to limit the analysis resources, a method for ranking of objects for maintenance analysis is needed. Preliminary suggestions for changes in maintenance action programs are based on signals from simple maintenance indicators and qualitative analysis of underlying data on failures and maintenance. To facilitate generation of maintenance indicators, and make the maintenance analysis more efficient, a powerful and suitable data treatment tool is needed for analysis of the work order history. In the final maintenance decisions, additional decision criteria must be taken into account, and thus a more formal decision analysis is often needed for decision support. (au)

Investigation of Multi-Criteria Decision Consistency: A Triplex Approach to Optimal Oilfield Portfolio Investment Decisions

Science.gov (United States)

Qaradaghi, Mohammed

Complexity of the capital intensive oil and gas portfolio investments is continuously growing. It is manifested in the constant increase in the type, number and degree of risks and uncertainties, which consequently lead to more challenging decision making problems. A typical complex decision making problem in petroleum exploration and production (E&P) is the selection and prioritization of oilfields/projects in a portfolio investment. Prioritizing oilfields maybe required for different purposes, including the achievement of a targeted production and allocation of limited available development resources. These resources cannot be distributed evenly nor can they be allocated based on the oilfield size or production capacity alone since various other factors need to be considered simultaneously. These factors may include subsurface complexity, size of reservoir, plateau production and needed infrastructure in addition to other issues of strategic concern, such as socio-economic, environmental and fiscal policies, particularly when the decision making involves governments or national oil companies. Therefore, it would be imperative to employ decision aiding tools that not only address these factors, but also incorporate the decision makers' preferences clearly and accurately. However, the tools commonly used in project portfolio selection and optimization, including intuitive approaches, vary in their focus and strength in addressing the different criteria involved in such decision problems. They are also disadvantaged by a number of drawbacks, which may include lacking the capacity to address multiple and interrelated criteria, uncertainty and risk, project relationship with regard to value contribution and optimum resource utilization, non-monetary attributes, decision maker's knowledge and expertise, in addition to varying levels of ease of use and other practical and theoretical drawbacks. These drawbacks have motivated researchers to investigate other tools and

An Introduction to Solar Decision-Making Tools

Energy Technology Data Exchange (ETDEWEB)

Mow, Benjamin [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-09-12

The National Renewable Energy Laboratory (NREL) offers a variety of models and analysis tools to help decision makers evaluate and make informed decisions about solar projects, policies, and programs. This fact sheet aims to help decision makers determine which NREL tool to use for a given solar project or policy question, depending on its scope.

Confronting dynamics and uncertainty in optimal decision making for conservation

Science.gov (United States)

Williams, Byron K.; Johnson, Fred A.

2013-06-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a

Confronting dynamics and uncertainty in optimal decision making for conservation

Science.gov (United States)

Williams, Byron K.; Johnson, Fred A.

2013-01-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a

Confronting dynamics and uncertainty in optimal decision making for conservation

International Nuclear Information System (INIS)

Williams, Byron K; Johnson, Fred A

2013-01-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a

Robust Inventory System Optimization Based on Simulation and Multiple Criteria Decision Making

Directory of Open Access Journals (Sweden)

Ahmad Mortazavi

2014-01-01

Full Text Available Inventory management in retailers is difficult and complex decision making process which is related to the conflict criteria, also existence of cyclic changes and trend in demand is inevitable in many industries. In this paper, simulation modeling is considered as efficient tool for modeling of retailer multiproduct inventory system. For simulation model optimization, a novel multicriteria and robust surrogate model is designed based on multiple attribute decision making (MADM method, design of experiments (DOE, and principal component analysis (PCA. This approach as a main contribution of this paper, provides a framework for robust multiple criteria decision making under uncertainty.

Decision-support tools for climate change mitigation planning

DEFF Research Database (Denmark)

Puig, Daniel; Aparcana Robles, Sandra Roxana

. For example, in the case of life-cycle analysis, the evaluation criterion entails that the impacts of interest are examined across the entire life-cycle of the product under study, from extraction of raw materials, to product disposal. Effectively, then, the choice of decision-support tool directs......This document describes three decision-support tools that can aid the process of planning climate change mitigation actions. The phrase ‘decision-support tools’ refers to science-based analytical procedures that facilitate the evaluation of planning options (individually or compared to alternative...... options) against a particular evaluation criterion or set of criteria. Most often decision-support tools are applied with the help of purpose-designed software packages and drawing on specialised databases.The evaluation criteria alluded to above define and characterise each decision-support tool...

Semiquantitative Decision Tools for FMD Emergency Vaccination Informed by Field Observations and Simulated Outbreak Data

DEFF Research Database (Denmark)

Willeberg, Preben; AlKhamis, Mohammad; Boklund, Anette

2017-01-01

We present two simple, semiquantitative model-based decision tools, based on the principle of first 14 days incidence (FFI). The aim is to estimate the likelihood and the consequences, respectively, of the ultimate size of an ongoing FMD epidemic. The tools allow risk assessors to communicate...... and optimize the presentation of the resulting data for urgent decisions to be made by the risk managers, we estimated the sensitivity, specificity, as well as the negative and positive predictive values, using a chosen day-14 outbreak number as predictor of the magnitude of the number of remaining post-day-14...

Decision-support tool for assessing future nuclear reactor generation portfolios

International Nuclear Information System (INIS)

Jain, Shashi; Roelofs, Ferry; Oosterlee, Cornelis W.

2014-01-01

Capital costs, fuel, operation and maintenance (O and M) costs, and electricity prices play a key role in the economics of nuclear power plants. Often standardized reactor designs are required to be locally adapted, which often impacts the project plans and the supply chain. It then becomes difficult to ascertain how these changes will eventually reflect in costs, which makes the capital costs component of nuclear power plants uncertain. Different nuclear reactor types compete economically by having either lower and less uncertain construction costs, increased efficiencies, lower and less uncertain fuel cycles and O and M costs etc. The decision making process related to nuclear power plants requires a holistic approach that takes into account the key economic factors and their uncertainties. We here present a decision-support tool that satisfactorily takes into account the major uncertainties in the cost elements of a nuclear power plant, to provide an optimal portfolio of nuclear reactors. The portfolio so obtained, under our model assumptions and the constraints considered, maximizes the combined returns for a given level of risk or uncertainty. These decisions are made using a combination of real option theory and mean–variance portfolio optimization. - Highlights: • Decisions to continue or abandon the construction of NPPs • Mean–variance portfolio of nuclear reactors • Sensitivity study of mean–variance portfolio of nuclear reactors

Optimizing perioperative decision making: improved information for clinical workflow planning.

Science.gov (United States)

Doebbeling, Bradley N; Burton, Matthew M; Wiebke, Eric A; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

2012-01-01

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40-70% of hospital revenues and 30-40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction.

Decision support frameworks and tools for conservation

Science.gov (United States)

Schwartz, Mark W.; Cook, Carly N.; Pressey, Robert L.; Pullin, Andrew S.; Runge, Michael C.; Salafsky, Nick; Sutherland, William J.; Williamson, Matthew A.

2018-01-01

The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.

A risk-based decision-aiding tool for waste disposal

International Nuclear Information System (INIS)

Weiner, R.F.; Reiser, A.S.; Elcock, C.G.; Nevins, S.

1997-01-01

N-CART (the National Spent Nuclear Fuel Program Cost Analysis and Risk Tool) is being developed to aid in low-risk, cost-effective, timely management of radioactive waste and spent nuclear fuel, and can therefore be used in management of mixed waste. N-CART provides evaluation of multiple alternatives and presents the consequences of proposed waste management activities in a clear and concise format. N-CART's decision-aiding analyses include comparisons and sensitivity analyses of multiple alternatives and allows the user to perform quick turn-around open-quotes what ifclose quotes studies to investigate various scenarios. Uncertainties in data (such as cost and schedule of various activities) are represented as distributions. N-CART centralizes documentation of the bases of program alternatives and program decisions, thereby supporting responses to stakeholders concerns. The initial N-CART design considers regulatory requirements, costs, and schedules for alternative courses of action. The final design will include risks (public health, occupational, economic, scheduling), economic benefits, and the impacts of secondary waste generation. An optimization tool is being incorporated that allows the user to specify the relative importance of cost, time risks, and other bases for decisions. The N-CART prototype can be used to compare the costs and schedules of disposal alternatives for mixed low-level radioactive waste (MLLW) and greater-than-Class-C (GTCC) waste, as well as spent nuclear fuel (SNF) and related scrap material

Contingency Contractor Optimization Phase 3 Sustainment Platform Requirements - Contingency Contractor Optimization Tool - Prototype

Energy Technology Data Exchange (ETDEWEB)

Durfee, Justin David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Frazier, Christopher Rawls [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bandlow, Alisa [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gearhart, Jared Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Katherine A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-06-01

Sandia National Laboratories (Sandia) is in Phase 3 Sustainment of development of a prototype tool, currently referred to as the Contingency Contractor Optimization Tool - Prototype (CCOTP), under the direction of OSD Program Support. CCOT-P is intended to help provide senior Department of Defense (DoD) leaders with comprehensive insight into the global availability, readiness and capabilities of the Total Force Mix. The CCOT-P will allow senior decision makers to quickly and accurately assess the impacts, risks and mitigating strategies for proposed changes to force/capabilities assignments, apportionments and allocations options, focusing specifically on contingency contractor planning. During Phase 2 of the program, conducted during fiscal year 2012, Sandia developed an electronic storyboard prototype of the Contingency Contractor Optimization Tool that can be used for communication with senior decision makers and other Operational Contract Support (OCS) stakeholders. Phase 3 used feedback from demonstrations of the electronic storyboard prototype to develop an engineering prototype for planners to evaluate. Sandia worked with the DoD and Joint Chiefs of Staff strategic planning community to get feedback and input to ensure that the engineering prototype was developed to closely align with future planning needs. The intended deployment environment was also a key consideration as this prototype was developed. Initial release of the engineering prototype was done on servers at Sandia in the middle of Phase 3. In 2013, the tool was installed on a production pilot server managed by the OUSD(AT&L) eBusiness Center. The purpose of this document is to specify the CCOT-P engineering prototype platform requirements as of May 2016. Sandia developed the CCOT-P engineering prototype using common technologies to minimize the likelihood of deployment issues. CCOT-P engineering prototype was architected and designed to be as independent as possible of the major deployment

A review of decision support, risk communication and patient information tools for thrombolytic treatment in acute stroke: lessons for tool developers.

Science.gov (United States)

Flynn, Darren; Ford, Gary A; Stobbart, Lynne; Rodgers, Helen; Murtagh, Madeleine J; Thomson, Richard G

2013-06-18

Tools to support clinical or patient decision-making in the treatment/management of a health condition are used in a range of clinical settings for numerous preference-sensitive healthcare decisions. Their impact in clinical practice is largely dependent on their quality across a range of domains. We critically analysed currently available tools to support decision making or patient understanding in the treatment of acute ischaemic stroke with intravenous thrombolysis, as an exemplar to provide clinicians/researchers with practical guidance on development, evaluation and implementation of such tools for other preference-sensitive treatment options/decisions in different clinical contexts. Tools were identified from bibliographic databases, Internet searches and a survey of UK and North American stroke networks. Two reviewers critically analysed tools to establish: information on benefits/risks of thrombolysis included in tools, and the methods used to convey probabilistic information (verbal descriptors, numerical and graphical); adherence to guidance on presenting outcome probabilities (IPDASi probabilities items) and information content (Picker Institute Checklist); readability (Fog Index); and the extent that tools had comprehensive development processes. Nine tools of 26 identified included information on a full range of benefits/risks of thrombolysis. Verbal descriptors, frequencies and percentages were used to convey probabilistic information in 20, 19 and 18 tools respectively, whilst nine used graphical methods. Shortcomings in presentation of outcome probabilities (e.g. omitting outcomes without treatment) were identified. Patient information tools had an aggregate median Fog index score of 10. None of the tools had comprehensive development processes. Tools to support decision making or patient understanding in the treatment of acute stroke with thrombolysis have been sub-optimally developed. Development of tools should utilise mixed methods and

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

Science.gov (United States)

Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

Science.gov (United States)

Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

2016-06-01

With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

Comparison of Greedy Algorithms for Decision Tree Optimization

KAUST Repository

Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail

2013-01-01

This chapter is devoted to the study of 16 types of greedy algorithms for decision tree construction. The dynamic programming approach is used for construction of optimal decision trees. Optimization is performed relative to minimal values

Tools for collaborative decision-making

CERN Document Server

Zaraté, Pascale

2013-01-01

Decision-making has evolved recently thanks to the introduction of information and communication technologies in many organizations, which has led to new kinds of decision-making processes, called "collaborative decision-making", at the organizational and cognitive levels. This book looks at the development of the decision-making process in organizations. Decision-aiding and its paradigm of problem solving are defined, showing how decision-makers now need to work in a cooperative way. Definitions of cooperation and associated concepts such as collaboration and coordination are given and a framework of cooperative decision support systems is presented, including intelligent DSS, cooperative knowledge-based systems, workflow, group support systems, collaborative engineering, integrating with a collaborative decision-making model in part or being part of global projects. Several models and experimental studies are also included showing that these new processes have to be supported by new types of tools, several ...

Decision support tool for soil sampling of heterogeneous pesticide (chlordecone) pollution.

Science.gov (United States)

Clostre, Florence; Lesueur-Jannoyer, Magalie; Achard, Raphaël; Letourmy, Philippe; Cabidoche, Yves-Marie; Cattan, Philippe

2014-02-01

When field pollution is heterogeneous due to localized pesticide application, as is the case of chlordecone (CLD), the mean level of pollution is difficult to assess. Our objective was to design a decision support tool to optimize soil sampling. We analyzed the CLD heterogeneity of soil content at 0-30- and 30-60-cm depth. This was done within and between nine plots (0.4 to 1.8 ha) on andosol and ferralsol. We determined that 20 pooled subsamples per plot were a satisfactory compromise with respect to both cost and accuracy. Globally, CLD content was greater for andosols and the upper soil horizon (0-30 cm). Soil organic carbon cannot account for CLD intra-field variability. Cropping systems and tillage practices influence the CLD content and distribution; that is CLD pollution was higher under intensive banana cropping systems and, while upper soil horizon was more polluted than the lower one with shallow tillage (pollution in the soil profile. The decision tool we proposed compiles and organizes these results to better assess CLD soil pollution in terms of sampling depth, distance, and unit at field scale. It accounts for sampling objectives, farming practices (cropping system, tillage), type of soil, and topographical characteristics (slope) to design a relevant sampling plan. This decision support tool is also adaptable to other types of heterogeneous agricultural pollution at field level.

Decision Analysis Tools for Volcano Observatories

Science.gov (United States)

Hincks, T. H.; Aspinall, W.; Woo, G.

2005-12-01

Staff at volcano observatories are predominantly engaged in scientific activities related to volcano monitoring and instrumentation, data acquisition and analysis. Accordingly, the academic education and professional training of observatory staff tend to focus on these scientific functions. From time to time, however, staff may be called upon to provide decision support to government officials responsible for civil protection. Recognizing that Earth scientists may have limited technical familiarity with formal decision analysis methods, specialist software tools that assist decision support in a crisis should be welcome. A review is given of two software tools that have been under development recently. The first is for probabilistic risk assessment of human and economic loss from volcanic eruptions, and is of practical use in short and medium-term risk-informed planning of exclusion zones, post-disaster response, etc. A multiple branch event-tree architecture for the software, together with a formalism for ascribing probabilities to branches, have been developed within the context of the European Community EXPLORIS project. The second software tool utilizes the principles of the Bayesian Belief Network (BBN) for evidence-based assessment of volcanic state and probabilistic threat evaluation. This is of practical application in short-term volcano hazard forecasting and real-time crisis management, including the difficult challenge of deciding when an eruption is over. An open-source BBN library is the software foundation for this tool, which is capable of combining synoptically different strands of observational data from diverse monitoring sources. A conceptual vision is presented of the practical deployment of these decision analysis tools in a future volcano observatory environment. Summary retrospective analyses are given of previous volcanic crises to illustrate the hazard and risk insights gained from use of these tools.

Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining

KAUST Repository

Hussain, Shahid

2016-01-01

This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.

Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining

KAUST Repository

Hussain, Shahid

2016-07-10

This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.

Tools of the Future: How Decision Tree Analysis Will Impact Mission Planning

Science.gov (United States)

Otterstatter, Matthew R.

2005-01-01

The universe is infinitely complex; however, the human mind has a finite capacity. The multitude of possible variables, metrics, and procedures in mission planning are far too many to address exhaustively. This is unfortunate because, in general, considering more possibilities leads to more accurate and more powerful results. To compensate, we can get more insightful results by employing our greatest tool, the computer. The power of the computer will be utilized through a technology that considers every possibility, decision tree analysis. Although decision trees have been used in many other fields, this is innovative for space mission planning. Because this is a new strategy, no existing software is able to completely accommodate all of the requirements. This was determined through extensive research and testing of current technologies. It was necessary to create original software, for which a short-term model was finished this summer. The model was built into Microsoft Excel to take advantage of the familiar graphical interface for user input, computation, and viewing output. Macros were written to automate the process of tree construction, optimization, and presentation. The results are useful and promising. If this tool is successfully implemented in mission planning, our reliance on old-fashioned heuristics, an error-prone shortcut for handling complexity, will be reduced. The computer algorithms involved in decision trees will revolutionize mission planning. The planning will be faster and smarter, leading to optimized missions with the potential for more valuable data.

Integrating decision management with UML modeling concepts and tools

DEFF Research Database (Denmark)

Könemann, Patrick

2009-01-01

, but also for guiding the user by proposing subsequent decisions. In model-based software development, many decisions directly affect the structural and behavioral models used to describe and develop a software system and its architecture. However, the decisions are typically not connected to these models...... of formerly disconnected tools could improve tool usability as well as decision maker productivity....

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Human Space Flight Missions

Science.gov (United States)

Kerstman, Eric L.; Minard, Charles; FreiredeCarvalho, Mary H.; Walton, Marlei E.; Myers, Jerry G., Jr.; Saile, Lynn G.; Lopez, Vilma; Butler, Douglas J.; Johnson-Throop, Kathy A.

2011-01-01

This slide presentation reviews the Integrated Medical Model (IMM) and its use as a risk assessment and decision support tool for human space flight missions. The IMM is an integrated, quantified, evidence-based decision support tool useful to NASA crew health and mission planners. It is intended to assist in optimizing crew health, safety and mission success within the constraints of the space flight environment for in-flight operations. It uses ISS data to assist in planning for the Exploration Program and it is not intended to assist in post flight research. The IMM was used to update Probability Risk Assessment (PRA) for the purpose of updating forecasts for the conditions requiring evacuation (EVAC) or Loss of Crew Life (LOC) for the ISS. The IMM validation approach includes comparison with actual events and involves both qualitative and quantitaive approaches. The results of these comparisons are reviewed. Another use of the IMM is to optimize the medical kits taking into consideration the specific mission and the crew profile. An example of the use of the IMM to optimize the medical kits is reviewed.

Dispositional optimism, self-framing and medical decision-making.

Science.gov (United States)

Zhao, Xu; Huang, Chunlei; Li, Xuesong; Zhao, Xin; Peng, Jiaxi

2015-03-01

Self-framing is an important but underinvestigated area in risk communication and behavioural decision-making, especially in medical settings. The present study aimed to investigate the relationship among dispositional optimism, self-frame and decision-making. Participants (N = 500) responded to the Life Orientation Test-Revised and self-framing test of medical decision-making problem. The participants whose scores were higher than the middle value were regarded as highly optimistic individuals. The rest were regarded as low optimistic individuals. The results showed that compared to the high dispositional optimism group, participants from the low dispositional optimism group showed a greater tendency to use negative vocabulary to construct their self-frame, and tended to choose the radiation therapy with high treatment survival rate, but low 5-year survival rate. Based on the current findings, it can be concluded that self-framing effect still exists in medical situation and individual differences in dispositional optimism can influence the processing of information in a framed decision task, as well as risky decision-making. © 2014 International Union of Psychological Science.

Selecting a risk-based tool to aid in decision making

Energy Technology Data Exchange (ETDEWEB)

Bendure, A.O.

1995-03-01

Selecting a risk-based tool to aid in decision making is as much of a challenge as properly using the tool once it has been selected. Failure to consider customer and stakeholder requirements and the technical bases and differences in risk-based decision making tools will produce confounding and/or politically unacceptable results when the tool is used. Selecting a risk-based decisionmaking tool must therefore be undertaken with the same, if not greater, rigor than the use of the tool once it is selected. This paper presents a process for selecting a risk-based tool appropriate to a set of prioritization or resource allocation tasks, discusses the results of applying the process to four risk-based decision-making tools, and identifies the ``musts`` for successful selection and implementation of a risk-based tool to aid in decision making.

Evaluation of the Effectiveness of Stormwater Decision Support Tools for Infrastructure Selection and the Barriers to Implementation

Science.gov (United States)

Spahr, K.; Hogue, T. S.

2016-12-01

Selecting the most appropriate green, gray, and / or hybrid system for stormwater treatment and conveyance can prove challenging to decision markers across all scales, from site managers to large municipalities. To help streamline the selection process, a multi-disciplinary team of academics and professionals is developing an industry standard for selecting and evaluating the most appropriate stormwater management technology for different regions. To make the tool more robust and comprehensive, life-cycle cost assessment and optimization modules will be included to evaluate non-monetized and ecosystem benefits of selected technologies. Initial work includes surveying advisory board members based in cities that use existing decision support tools in their infrastructure planning process. These surveys will qualify the decisions currently being made and identify challenges within the current planning process across a range of hydroclimatic regions and city size. Analysis of social and other non-technical barriers to adoption of the existing tools is also being performed, with identification of regional differences and institutional challenges. Surveys will also gage the regional appropriateness of certain stormwater technologies based off experiences in implementing stormwater treatment and conveyance plans. In additional to compiling qualitative data on existing decision support tools, a technical review of components of the decision support tool used will be performed. Gaps in each tool's analysis, like the lack of certain critical functionalities, will be identified and ease of use will be evaluated. Conclusions drawn from both the qualitative and quantitative analyses will be used to inform the development of the new decision support tool and its eventual dissemination.

Computer-based tools for decision support at the Hanford Site

International Nuclear Information System (INIS)

Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

1992-11-01

To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high' level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the ''glue'' or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission

Computer-based tools for decision support at the Hanford Site

Energy Technology Data Exchange (ETDEWEB)

Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

1992-11-01

To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high' level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the glue'' or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

Computer-based tools for decision support at the Hanford Site

Energy Technology Data Exchange (ETDEWEB)

Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

1992-11-01

To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high` level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the ``glue`` or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

Totally optimal decision trees for Boolean functions

KAUST Repository

Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2016-01-01

We study decision trees which are totally optimal relative to different sets of complexity parameters for Boolean functions. A totally optimal tree is an optimal tree relative to each parameter from the set simultaneously. We consider the parameters

Application of MCDM based hybrid optimization tool during turning of ASTM A588

Directory of Open Access Journals (Sweden)

Himadri Majumder

2017-07-01

Full Text Available Multi-criteria decision making approach is one of the most troublesome tools for solving the tangled optimization problems in the machining area due to its capability of solving the complex optimization problems in the production process. Turning is widely used in the manufacturing processes as it offers enormous advantages like good quality product, customer satisfaction, economical and relatively easy to apply. A contemporary approach, MOORA coupled with PCA, was used to ascertain an optimal combination of input parameters (spindle speed, depth of cut and feed rate for the given output parameters (power consumption, average surface roughness and frequency of tool vibration using L27 orthogonal array for turning on ASTM A588 mild steel. Comparison between MOORA-PCA and TOPSIS-PCA shows the effectiveness of MOORA over TOPSIS method. The optimum parameter combination for multi-performance characteristics has been established for ASTM A588 mild steel are spindle speed 160 rpm, depth of cut 0.1 mm and feed rate 0.08 mm/rev. Therefore, this study focuses on the application of the hybrid MCDM approach as a vital selection making tool to deal with multi objective optimization problems.

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

Science.gov (United States)

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

Determining Optimal Decision Version

Directory of Open Access Journals (Sweden)

Olga Ioana Amariei

2014-06-01

Full Text Available In this paper we start from the calculation of the product cost, applying the method of calculating the cost of hour- machine (THM, on each of the three cutting machines, namely: the cutting machine with plasma, the combined cutting machine (plasma and water jet and the cutting machine with a water jet. Following the calculation of cost and taking into account the precision of manufacturing of each machine, as well as the quality of the processed surface, the optimal decisional version needs to be determined regarding the product manufacturing. To determine the optimal decisional version, we resort firstly to calculating the optimal version on each criterion, and then overall using multiattribute decision methods.

An ArcGIS decision support tool for artificial reefs site selection (ArcGIS ARSS)

Science.gov (United States)

Stylianou, Stavros; Zodiatis, George

2017-04-01

Although the use and benefits of artificial reefs, both socio-economic and environmental, have been recognized with research and national development programmes worldwide their development is rarely subjected to a rigorous site selection process and the majority of the projects use the traditional (non-GIS) approach, based on trial and error mode. Recent studies have shown that the use of Geographic Information Systems, unlike to traditional methods, for the identification of suitable areas for artificial reefs siting seems to offer a number of distinct advantages minimizing possible errors, time and cost. A decision support tool (DSS) has been developed based on the existing knowledge, the multi-criteria decision analysis techniques and the GIS approach used in previous studies in order to help the stakeholders to identify the optimal locations for artificial reefs deployment on the basis of the physical, biological, oceanographic and socio-economic features of the sites. The tool provides to the users the ability to produce a final report with the results and suitability maps. The ArcGIS ARSS support tool runs within the existing ArcMap 10.2.x environment and for the development the VB .NET high level programming language has been used along with ArcObjects 10.2.x. Two local-scale case studies were conducted in order to test the application of the tool focusing on artificial reef siting. The results obtained from the case studies have shown that the tool can be successfully integrated within the site selection process in order to select objectively the optimal site for artificial reefs deployment.

Human Decision Processes: Implications for SSA Support Tools

Science.gov (United States)

Picciano, P.

2013-09-01

paper), one opinion shared is that the rational, economic, deliberate listing/evaluation of all options is NOT representative of how many decision are made. A framework gaining interest lately describes two systems predominantly at work: intuition and reasoning (Kahneman, 2003). Intuition is fast, automatic, and parallel contrasted with the more effortful, deliberative, and sequential reasoning. One of the issues of contention is that considerable research is stacked supporting both sides claiming that intuition is: • A hallmark of expertise responsible for rapid, optimal decisions in the face of adversity • A vulnerability where biases serve as decision traps leading to wrong choices Using seminal studies from a range of domains and tasking, potential solutions for SSA decision support will be offered. Important issues such as managing uncertainty, framing inquiries, and information architecture, and contextual cues will be discussed. The purpose is to provide awareness of the human limitations and capabilities in complex decision making so engineers and designers can consider such factors in their development of SSA tools.

Unrealistic optimism and decision making

Directory of Open Access Journals (Sweden)

Božović Bojana

2009-01-01

Full Text Available One of the leading descriptive theories of decision-making under risk, Tversky & Kahneman's Prospect theory, reveals that normative explanation of decisionmaking, based only on principle of maximizing outcomes expected utility, is unsustainable. It also underlines the effect of alternative factors on decision-making. Framing effect relates to an influence that verbal formulation of outcomes has on choosing between certain and risky outcomes; in negative frame people tend to be risk seeking, whereas in positive frame people express risk averse tendencies. Individual decisions are not based on objective probabilities of outcomes, but on subjective probabilities that depend on outcome desirability. Unrealistically pessimistic subjects assign lower probabilities (than the group average to the desired outcomes, while unrealistically optimistic subjects assign higher probabilities (than the group average to the desired outcomes. Experiment was conducted in order to test the presumption that there's a relation between unrealistic optimism and decision-making under risk. We expected optimists to be risk seeking, and pessimist to be risk averse. We also expected such cognitive tendencies, if they should become manifest, to be framing effect resistant. Unrealistic optimism scale was applied, followed by the questionnaire composed of tasks of decision-making under risk. Results within the whole sample, and results of afterwards extracted groups of pessimists and optimists both revealed dominant risk seeking tendency that is resistant to the influence of subjective probabilities as well as to the influence of frame in which the outcome is presented.

Minimization of decision tree depth for multi-label decision tables

KAUST Repository

Azad, Mohammad

2014-10-01

In this paper, we consider multi-label decision tables that have a set of decisions attached to each row. Our goal is to find one decision from the set of decisions for each row by using decision tree as our tool. Considering our target to minimize the depth of the decision tree, we devised various kinds of greedy algorithms as well as dynamic programming algorithm. When we compare with the optimal result obtained from dynamic programming algorithm, we found some greedy algorithms produces results which are close to the optimal result for the minimization of depth of decision trees.

Minimization of decision tree depth for multi-label decision tables

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2014-01-01

In this paper, we consider multi-label decision tables that have a set of decisions attached to each row. Our goal is to find one decision from the set of decisions for each row by using decision tree as our tool. Considering our target to minimize the depth of the decision tree, we devised various kinds of greedy algorithms as well as dynamic programming algorithm. When we compare with the optimal result obtained from dynamic programming algorithm, we found some greedy algorithms produces results which are close to the optimal result for the minimization of depth of decision trees.

Development and field testing of a decision support tool to facilitate shared decision making in contraceptive counseling.

Science.gov (United States)

Dehlendorf, Christine; Fitzpatrick, Judith; Steinauer, Jody; Swiader, Lawrence; Grumbach, Kevin; Hall, Cara; Kuppermann, Miriam

2017-07-01

We developed and formatively evaluated a tablet-based decision support tool for use by women prior to a contraceptive counseling visit to help them engage in shared decision making regarding method selection. Drawing upon formative work around women's preferences for contraceptive counseling and conceptual understanding of health care decision making, we iteratively developed a storyboard and then digital prototypes, based on best practices for decision support tool development. Pilot testing using both quantitative and qualitative data and cognitive testing was conducted. We obtained feedback from patient and provider advisory groups throughout the development process. Ninety-six percent of women who used the tool in pilot testing reported that it helped them choose a method, and qualitative interviews indicated acceptability of the tool's content and presentation. Compared to the control group, women who used the tool demonstrated trends toward increased likelihood of complete satisfaction with their method. Participant responses to cognitive testing were used in tool refinement. Our decision support tool appears acceptable to women in the family planning setting. Formative evaluation of the tool supports its utility among patients making contraceptive decisions, which can be further evaluated in a randomized controlled trial. Copyright © 2017 Elsevier B.V. All rights reserved.

Decision-making on olympic urban development - multi-actor decision support tool

NARCIS (Netherlands)

Heurkens, E.W.T.M.

Subject of study is the possible organisation of the Olympic Games of 2028 in the Netherlands, as seen from an urban development viewpoint. The project focuses on the decision-making process in the initiative phase. Aim of the project is the development of a decision support tool for the complex,

Security constrained optimal power flow by modern optimization tools

African Journals Online (AJOL)

Security constrained optimal power flow by modern optimization tools. ... International Journal of Engineering, Science and Technology ... If you would like more information about how to print, save, and work with PDFs, Highwire Press ...

On algorithm for building of optimal α-decision trees

KAUST Repository

Alkhalid, Abdulaziz

2010-01-01

The paper describes an algorithm that constructs approximate decision trees (α-decision trees), which are optimal relatively to one of the following complexity measures: depth, total path length or number of nodes. The algorithm uses dynamic programming and extends methods described in [4] to constructing approximate decision trees. Adjustable approximation rate allows controlling algorithm complexity. The algorithm is applied to build optimal α-decision trees for two data sets from UCI Machine Learning Repository [1]. © 2010 Springer-Verlag Berlin Heidelberg.

Usability Testing of a Complex Clinical Decision Support Tool in the Emergency Department: Lessons Learned.

Science.gov (United States)

Press, Anne; McCullagh, Lauren; Khan, Sundas; Schachter, Andy; Pardo, Salvatore; McGinn, Thomas

2015-09-10

the Wells tool in assessing a patient for a PE diagnosis. Subjects described the tool as "well-organized" and "better than clinical judgment". Changes were made to improve tool placement into the EHR to make it optimal for decision-making, auto-populating boxes, and minimizing click fatigue. Phase II: After incorporating the changes noted in Phase 1, the participants noted tool improvements. There was less toggling between screens, they had all the clinical information required to complete the tool, and were able to complete the patient visit efficiently. However, an optimal location for triggering the tool remained controversial. This study successfully combined "think-aloud" protocol analysis with "near-live" clinical simulations in a usability evaluation of a CDS tool that will be implemented into the emergency room environment. Both methods proved useful in the assessment of the CDS tool and allowed us to refine tool usability and workflow.

Virtual Beach: Decision Support Tools for Beach Pathogen Prediction

Science.gov (United States)

The Virtual Beach Managers Tool (VB) is decision-making software developed to help local beach managers make decisions as to when beaches should be closed due to predicted high levels of water borne pathogens. The tool is being developed under the umbrella of EPA's Advanced Monit...

A Decision Support Tool for Appropriate Glucose-Lowering Therapy in Patients with Type 2 Diabetes

DEFF Research Database (Denmark)

Ampudia-Blasco, F Javier; Benhamou, Pierre Yves; Charpentier, Guillaume

2014-01-01

Abstract Background: Optimal glucose-lowering therapy in type 2 diabetes mellitus requires a patient-specific approach. Although a good framework, current guidelines are insufficiently detailed to address the different phenotypes and individual needs of patients seen in daily practice. We developed...... a patient-specific decision support tool based on a systematic analysis of expert opinion. Materials and Methods: Based on the American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) 2012 position statement, a panel of 12 European experts rated the appropriateness (RAND....... The panel recommendations were embedded in an online decision support tool (DiaScope(®); Novo Nordisk Health Care AG, Zürich, Switzerland). Results: Treatment appropriateness was associated with (combinations of) the patient variables mentioned above. As second-line agents, dipeptidyl peptidase-4 inhibitors...

Dynamic programming approach for partial decision rule optimization

KAUST Repository

Amin, Talha

2012-10-04

This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

Dynamic programming approach for partial decision rule optimization

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2012-01-01

This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

Designing decision support tools for targeted N-regulation

DEFF Research Database (Denmark)

Christensen, Andreas Aagaard; Piil, Kristoffer; Andersen, Peter Stubkjær

2017-01-01

data model for land use data – the dNmark landscape model. Based on input data which is corrected and edited by workshop participants, the tool estimates the effect of potential land use scenarios on nutrient emissions. The tool was tested in 5 scenario workshops in case areas in Denmark in 2016...... in Denmark to develop and improve a functioning decision support tool for landscape scale N-management. The aim of the study is to evaluate how a decision support tool can best be designed in order to enable landscape scale strategic N-management practices. Methods: A prototype GIS-tool for capturing......, storing, editing, displaying and modelling landscape scale farming practices and associated emission consequences was developed. The tool was designed to integrate locally held knowledge with national scale datasets in live scenario situations through the implementation of a flexible, uniform and editable...

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha

2013-11-25

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Benefits and limitations of using decision analytic tools to assess uncertainty and prioritize Landscape Conservation Cooperative information needs

Science.gov (United States)

Post van der Burg, Max; Cullinane Thomas, Catherine; Holcombe, Tracy R.; Nelson, Richard D.

2016-01-01

The Landscape Conservation Cooperatives (LCCs) are a network of partnerships throughout North America that are tasked with integrating science and management to support more effective delivery of conservation at a landscape scale. In order to achieve this integration, some LCCs have adopted the approach of providing their partners with better scientific information in an effort to facilitate more effective and coordinated conservation decisions. Taking this approach has led many LCCs to begin funding research to provide the information for improved decision making. To ensure that funding goes to research projects with the highest likelihood of leading to more integrated broad scale conservation, some LCCs have also developed approaches for prioritizing which information needs will be of most benefit to their partnerships. We describe two case studies in which decision analytic tools were used to quantitatively assess the relative importance of information for decisions made by partners in the Plains and Prairie Potholes LCC. The results of the case studies point toward a few valuable lessons in terms of using these tools with LCCs. Decision analytic tools tend to help shift focus away from research oriented discussions and toward discussions about how information is used in making better decisions. However, many technical experts do not have enough knowledge about decision making contexts to fully inform the latter type of discussion. When assessed in the right decision context, however, decision analyses can point out where uncertainties actually affect optimal decisions and where they do not. This helps technical experts understand that not all research is valuable in improving decision making. But perhaps most importantly, our results suggest that decision analytic tools may be more useful for LCCs as way of developing integrated objectives for coordinating partner decisions across the landscape, rather than simply ranking research priorities.

Designing Tools for Supporting User Decision-Making in e-Commerce

Science.gov (United States)

Sutcliffe, Alistair; Al-Qaed, Faisal

The paper describes a set of tools designed to support a variety of user decision-making strategies. The tools are complemented by an online advisor so they can be adapted to different domains and users can be guided to adopt appropriate tools for different choices in e-commerce, e.g. purchasing high-value products, exploring product fit to users’ needs, or selecting products which satisfy requirements. The tools range from simple recommenders to decision support by interactive querying and comparison matrices. They were evaluated in a scenario-based experiment which varied the users’ task and motivation, with and without an advisor agent. The results show the tools and advisor were effective in supporting users and agreed with the predictions of ADM (adaptive decision making) theory, on which the design of the tools was based.

Dynamic programming approach to optimization of approximate decision rules

KAUST Repository

Amin, Talha

2013-02-01

This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number of unordered pairs of rows with different decisions in the decision table T. For a nonnegative real number β, we consider β-decision rules that localize rows in subtables of T with uncertainty at most β. Our algorithm constructs a directed acyclic graph Δβ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most β. The graph Δβ(T) allows us to describe the whole set of so-called irredundant β-decision rules. We can describe all irredundant β-decision rules with minimum length, and after that among these rules describe all rules with maximum coverage. We can also change the order of optimization. The consideration of irredundant rules only does not change the results of optimization. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2012 Elsevier Inc. All rights reserved.

Classification and Optimization of Decision Trees for Inconsistent Decision Tables Represented as MVD Tables

KAUST Repository

Azad, Mohammad

2015-10-11

Decision tree is a widely used technique to discover patterns from consistent data set. But if the data set is inconsistent, where there are groups of examples (objects) with equal values of conditional attributes but different decisions (values of the decision attribute), then to discover the essential patterns or knowledge from the data set is challenging. We consider three approaches (generalized, most common and many-valued decision) to handle such inconsistency. We created different greedy algorithms using various types of impurity and uncertainty measures to construct decision trees. We compared the three approaches based on the decision tree properties of the depth, average depth and number of nodes. Based on the result of the comparison, we choose to work with the many-valued decision approach. Now to determine which greedy algorithms are efficient, we compared them based on the optimization and classification results. It was found that some greedy algorithms Mult\\\\_ws\\\\_entSort, and Mult\\\\_ws\\\\_entML are good for both optimization and classification.

Classification and Optimization of Decision Trees for Inconsistent Decision Tables Represented as MVD Tables

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2015-01-01

Decision tree is a widely used technique to discover patterns from consistent data set. But if the data set is inconsistent, where there are groups of examples (objects) with equal values of conditional attributes but different decisions (values of the decision attribute), then to discover the essential patterns or knowledge from the data set is challenging. We consider three approaches (generalized, most common and many-valued decision) to handle such inconsistency. We created different greedy algorithms using various types of impurity and uncertainty measures to construct decision trees. We compared the three approaches based on the decision tree properties of the depth, average depth and number of nodes. Based on the result of the comparison, we choose to work with the many-valued decision approach. Now to determine which greedy algorithms are efficient, we compared them based on the optimization and classification results. It was found that some greedy algorithms Mult\\_ws\\_entSort, and Mult\\_ws\\_entML are good for both optimization and classification.

Proposal optimization in nuclear accident emergency decision based on IAHP

International Nuclear Information System (INIS)

Xin Jing

2007-01-01

On the basis of establishing the multi-layer structure of nuclear accident emergency decision, several decision objectives are synthetically analyzed, and an optimization model of decision proposals for nuclear accident emergency based on interval analytic hierarchy process is proposed in the paper. The model makes comparisons among several emergency decision proposals quantified, and the optimum proposal is selected out, which solved the uncertain and fuzzy decision problem of judgments by experts' experiences in nuclear accidents emergency decision. Case study shows that the optimization result is much more reasonable, objective and reliable than subjective judgments, and it could be decision references for nuclear accident emergency. (authors)

Decision support tools in conservation: a workshop to improve user-centred design

Directory of Open Access Journals (Sweden)

David Rose

2017-09-01

Full Text Available A workshop held at the University of Cambridge in May 2017 brought developers, researchers, knowledge brokers, and users together to discuss user-centred design of decision support tools. Decision support tools are designed to take users through logical decision steps towards an evidence-informed final decision. Although they may exist in different forms, including on paper, decision support tools are generally considered to be computer- (online, software or app-based. Studies have illustrated the potential value of decision support tools for conservation, and there are several papers describing the design of individual tools. Rather less attention, however, has been placed on the desirable characteristics for use, and even less on whether tools are actually being used in practice. This is concerning because if tools are not used by their intended end user, for example a policy-maker or practitioner, then its design will have wasted resources. Based on an analysis of papers on tool use in conservation, there is a lack of social science research on improving design, and relatively few examples where users have been incorporated into the design process. Evidence from other disciplines, particularly human-computer interaction research, illustrates that involving users throughout the design of decision support tools increases the relevance, usability, and impact of systems. User-centred design of tools is, however, seldom mentioned in the conservation literature. The workshop started the necessary process of bringing together developers and users to share knowledge about how to conduct good user-centred design of decision support tools. This will help to ensure that tools are usable and make an impact in conservation policy and practice.

Multiobjective Optimization of Aircraft Maintenance in Thailand Using Goal Programming: A Decision-Support Model

Directory of Open Access Journals (Sweden)

Yuttapong Pleumpirom

2012-01-01

Full Text Available The purpose of this paper is to develop the multiobjective optimization model in order to evaluate suppliers for aircraft maintenance tasks, using goal programming. The authors have developed a two-step process. The model will firstly be used as a decision-support tool for managing demand, by using aircraft and flight schedules to evaluate and generate aircraft-maintenance requirements, including spare-part lists. Secondly, they develop a multiobjective optimization model by minimizing cost, minimizing lead time, and maximizing the quality under various constraints in the model. Finally, the model is implemented in the actual airline's case.

Comparison of Greedy Algorithms for Decision Tree Optimization

KAUST Repository

Alkhalid, Abdulaziz

2013-01-01

This chapter is devoted to the study of 16 types of greedy algorithms for decision tree construction. The dynamic programming approach is used for construction of optimal decision trees. Optimization is performed relative to minimal values of average depth, depth, number of nodes, number of terminal nodes, and number of nonterminal nodes of decision trees. We compare average depth, depth, number of nodes, number of terminal nodes and number of nonterminal nodes of constructed trees with minimum values of the considered parameters obtained based on a dynamic programming approach. We report experiments performed on data sets from UCI ML Repository and randomly generated binary decision tables. As a result, for depth, average depth, and number of nodes we propose a number of good heuristics. © Springer-Verlag Berlin Heidelberg 2013.

Accelerated bridge construction (ABC) decision making and economic modeling tool.

Science.gov (United States)

2011-12-01

In this FHWA-sponsored pool funded study, a set of decision making tools, based on the Analytic Hierarchy Process (AHP) was developed. This tool set is prepared for transportation specialists and decision-makers to determine if ABC is more effective ...

Optimizing asset value (OAV) -- A decision tool for mergers and acquisitions

Energy Technology Data Exchange (ETDEWEB)

Blanchard, D.; Brinsfield, W.; Franklin, E. [Tenera Energy, LLC, San Francisco, CA (United States); Turnage, J. [US Generating Co., Bethesda, MD (United States)

1999-11-01

As the energy industry restructures and realigns, companies are increasingly engaged in all aspects of mergers, acquisitions, and divestiture. Successful transactions are no accident, and new insights are emerging daily. This paper describes a tool called Optimizing Asset Value (OAV) that provides support to the Valuation phase of the merger, acquisition, and divestiture process. The methodology is based upon a quantitative, risk-based approach that is used to calculate the impact of equipment operation and operations/maintenance practices upon the ability to generate maximum revenue. By combining probabilistic reliability data with the economic consequences of plant derating, equipment can be prioritized as to its importance to revenue generation. Savvy buyers can apply OAV to plants under consideration for purchase to estimate where the plant is on its revenue generation capability curve, and thus gain a better understanding as to the risks, or opportunities for improvement, that exist. This information can be used along with other pro forma analyses to set the bid price for the asset.

Simultaneous Optimization of Decisions Using a Linear Utility Function.

Science.gov (United States)

Vos, Hans J.

1990-01-01

An approach is presented to simultaneously optimize decision rules for combinations of elementary decisions through a framework derived from Bayesian decision theory. The developed linear utility model for selection-mastery decisions was applied to a sample of 43 first year medical students to illustrate the procedure. (SLD)

A Global Multi-Objective Optimization Tool for Design of Mechatronic Components using Generalized Differential Evolution

DEFF Research Database (Denmark)

Bech, Michael Møller; Nørgård, Christian; Roemer, Daniel Beck

2016-01-01

This paper illustrates how the relatively simple constrained multi-objective optimization algorithm Generalized Differential Evolution 3 (GDE3), can assist with the practical sizing of mechatronic components used in e.g. digital displacement fluid power machinery. The studied bi- and tri-objectiv......This paper illustrates how the relatively simple constrained multi-objective optimization algorithm Generalized Differential Evolution 3 (GDE3), can assist with the practical sizing of mechatronic components used in e.g. digital displacement fluid power machinery. The studied bi- and tri...... different optimization control parameter settings and it is concluded that GDE3 is a reliable optimization tool that can assist mechatronic engineers in the design and decision making process....

Rotorcraft Optimization Tools: Incorporating Rotorcraft Design Codes into Multi-Disciplinary Design, Analysis, and Optimization

Science.gov (United States)

Meyn, Larry A.

2018-01-01

One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its use

A review of features in Internet consumer health decision-support tools.

Science.gov (United States)

Schwitzer, Gary

2002-01-01

Over the past decade, health care consumers have begun to benefit from new Web-based communications tools to guide decision making on treatments and tests. Using today's online tools, consumers who have Internet connections can: watch and listen to videos of physicians; watch and hear the stories of other consumers who have faced the same decisions; join an online social support network; receive estimates of their own chances of experiencing various outcomes; and do it all at home. To review currently-available Internet consumer health decision-support tools. Five Web sites offering consumer health decision-support tools are analyzed for their use of 4 key Web-enabled features: the presentation of outcomes probability data tailored to the individual user; the use of videotaped patient interviews in the final product to convey the experiences of people who have faced similar diagnoses in the past; the ability to interact with others in a social support network; and the accessibility of the tool to any health care consumers with an Internet connection. None of the 5 Web sites delivers all 4 target features to all Web users. The reasons for these variations in the use of key Web functionality--features that make the Web distinctive--are not immediately clear. Consumers trying to make health care decisions may benefit from current Web-based decision-support tools. But, variations in Web developers' use of 4 key Web-enabled features leaves the online decision-support experience less than what it could be. Key research questions are identified that could help in the development of new hybrid patient decision-support tools.

A complex systems approach to planning, optimization and decision making for energy networks

International Nuclear Information System (INIS)

Beck, Jessica; Kempener, Ruud; Cohen, Brett; Petrie, Jim

2008-01-01

This paper explores a new approach to planning and optimization of energy networks, using a mix of global optimization and agent-based modeling tools. This approach takes account of techno-economic, environmental and social criteria, and engages explicitly with inherent network complexity in terms of the autonomous decision-making capability of individual agents within the network, who may choose not to act as economic rationalists. This is an important consideration from the standpoint of meeting sustainable development goals. The approach attempts to set targets for energy planning, by determining preferred network development pathways through multi-objective optimization. The viability of such plans is then explored through agent-based models. The combined approach is demonstrated for a case study of regional electricity generation in South Africa, with biomass as feedstock

MARKET EVALUATION MODEL: TOOL FORBUSINESS DECISIONS

OpenAIRE

Porlles Loarte, José; Yenque Dedios, Julio; Lavado Soto, Aurelio

2014-01-01

In the present work the concepts of potential market and global market are analyzed as the basis for strategic decisions of market with long term perspectives, when the implantation of a business in certain geographic area is evaluated. On this conceptual frame, the methodological tool is proposed to evaluate a commercial decision, for which it is taken as reference the case from the brewing industry in Peru, considering that this industry faces in the region entrepreneurial reorderings withi...

Volatile decision dynamics: experiments, stochastic description, intermittency control and traffic optimization

Science.gov (United States)

Helbing, Dirk; Schönhof, Martin; Kern, Daniel

2002-06-01

The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision dynamics and far-from-optimal payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine optimal strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision dynamics. These results are highly significant for predicting decision behaviour, for reaching optimal behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic optimization.

Cost effectiveness of pediatric pneumococcal conjugate vaccines: a comparative assessment of decision-making tools.

Science.gov (United States)

Chaiyakunapruk, Nathorn; Somkrua, Ratchadaporn; Hutubessy, Raymond; Henao, Ana Maria; Hombach, Joachim; Melegaro, Alessia; Edmunds, John W; Beutels, Philippe

2011-05-12

Several decision support tools have been developed to aid policymaking regarding the adoption of pneumococcal conjugate vaccine (PCV) into national pediatric immunization programs. The lack of critical appraisal of these tools makes it difficult for decision makers to understand and choose between them. With the aim to guide policymakers on their optimal use, we compared publicly available decision-making tools in relation to their methods, influential parameters and results. The World Health Organization (WHO) requested access to several publicly available cost-effectiveness (CE) tools for PCV from both public and private provenance. All tools were critically assessed according to the WHO's guide for economic evaluations of immunization programs. Key attributes and characteristics were compared and a series of sensitivity analyses was performed to determine the main drivers of the results. The results were compared based on a standardized set of input parameters and assumptions. Three cost-effectiveness modeling tools were provided, including two cohort-based (Pan-American Health Organization (PAHO) ProVac Initiative TriVac, and PneumoADIP) and one population-based model (GlaxoSmithKline's SUPREMES). They all compared the introduction of PCV into national pediatric immunization program with no PCV use. The models were different in terms of model attributes, structure, and data requirement, but captured a similar range of diseases. Herd effects were estimated using different approaches in each model. The main driving parameters were vaccine efficacy against pneumococcal pneumonia, vaccine price, vaccine coverage, serotype coverage and disease burden. With a standardized set of input parameters developed for cohort modeling, TriVac and PneumoADIP produced similar incremental costs and health outcomes, and incremental cost-effectiveness ratios. Vaccine cost (dose price and number of doses), vaccine efficacy and epidemiology of critical endpoint (for example

Dynamic Programming Approach for Exact Decision Rule Optimization

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from

Collaboration pathway(s) using new tools for optimizing `operational' climate monitoring from space

Science.gov (United States)

Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.

2015-09-01

definitions of global coverages intended to ensure the needs of major global and international organizations (UNFCCC and IPCC) are met as a core objective. Consider how new optimization tools like rule-based engines (RBES) offer alternative methods of evaluating collaborative architectures and constellations? What would the trade space of optimized operational climate monitoring architectures of ECV look like? Third, using the RBES tool kit (2014) demonstrate with application to a climate centric rule-based decision engine - optimizing architectural trades of earth observation satellite systems, allowing comparison(s) to existing architectures and gaining insights for global collaborative architectures. How difficult is it to pull together an optimized climate case study - utilizing for example 12 climate based instruments on multiple existing platforms and nominal handful of orbits; for best cost and performance benefits against the collection requirements of representative set of ECV. How much effort and resources would an organization expect to invest to realize these analysis and utility benefits?

Study on Web-Based Tool for Regional Agriculture Industry Structure Optimization Using Ajax

Science.gov (United States)

Huang, Xiaodong; Zhu, Yeping

According to the research status of regional agriculture industry structure adjustment information system and the current development of information technology, this paper takes web-based regional agriculture industry structure optimization tool as research target. This paper introduces Ajax technology and related application frameworks to build an auxiliary toolkit of decision support system for agricultural policy maker and economy researcher. The toolkit includes a “one page” style component of regional agriculture industry structure optimization which provides agile arguments setting method that enables applying sensitivity analysis and usage of data and comparative advantage analysis result, and a component that can solve the linear programming model and its dual problem by simplex method.

International Conference on Optimization and Decision Science

CERN Document Server

Sterle, Claudio

2017-01-01

This proceedings volume highlights the state-of-the-art knowledge related to optimization, decisions science and problem solving methods, as well as their application in industrial and territorial systems. It includes contributions tackling these themes using models and methods based on continuous and discrete optimization, network optimization, simulation and system dynamics, heuristics, metaheuristics, artificial intelligence, analytics, and also multiple-criteria decision making. The number and the increasing size of the problems arising in real life require mathematical models and solution methods adequate to their complexity. There has also been increasing research interest in Big Data and related challenges. These challenges can be recognized in many fields and systems which have a significant impact on our way of living: design, management and control of industrial production of goods and services; transportation planning and traffic management in urban and regional areas; energy production and exploit...

On optimal soft-decision demodulation. [in digital communication system

Science.gov (United States)

Lee, L.-N.

1976-01-01

A necessary condition is derived for optimal J-ary coherent demodulation of M-ary (M greater than 2) signals. Optimality is defined as maximality of the symmetric cutoff rate of the resulting discrete memoryless channel. Using a counterexample, it is shown that the condition derived is generally not sufficient for optimality. This condition is employed as the basis for an iterative optimization method to find the optimal demodulator decision regions from an initial 'good guess'. In general, these regions are found to be bounded by hyperplanes in likelihood space; the corresponding regions in signal space are found to have hyperplane asymptotes for the important case of additive white Gaussian noise. Some examples are presented, showing that the regions in signal space bounded by these asymptotic hyperplanes define demodulator decision regions that are virtually optimal.

Towards life-cycle awareness in decision support tools for engineering design

OpenAIRE

Nergård, Henrik; Sandberg, Marcus; Larsson, Tobias

2009-01-01

In this paper a decision support tool with the focus on how to generate and visualize decision base coupled to the business agreement is outlined and discussed. Decision support tools for the early design phases are few and especially tools that visualize the readiness level of activities throughout the product life-cycle. Aiming for the sustainable society there is an indication that business-to-business manufacturers move toward providing a function rather than selling off the hardware and ...

Dispositional Optimism as a Correlate of Decision-Making Styles in Adolescence

Directory of Open Access Journals (Sweden)

Paola Magnano

2015-06-01

Full Text Available Despite the numerous psychological areas in which optimism has been studied, including career planning, only a small amount of research has been done to investigate the relationship between optimism and decision-making styles. Consequently, we have investigated the role of dispositional optimism as a correlate of different decision-making styles, in particular, positive for effective styles and negative for ineffective ones (doubtfulness, procrastination, and delegation. Data were gathered through questionnaires administered to 803 Italian adolescents in their last 2 years of high schools with different fields of study, each at the beginning stages of planning for their professional future. A paper questionnaire was completed containing measures of dispositional optimism and career-related decision styles, during a vocational guidance intervention conducted at school. Data were analyzed using stepwise multiple regression. Results supported the proposed model by showing optimism to be a strong correlate of decision-making styles, thereby offering important intervention guidelines aimed at modifying unrealistically negative expectations regarding their future and helping students learn adaptive decision-making skills.

Dynamic Material Removal Rate and Tool Replacement Optimization with Calculus of Variations

Science.gov (United States)

Lan, Tian-Syung; Lo, Chih-Yao; Chiu, Min-Chie; Yeh, Long-Jyi

This study mathematically presents an optimum material removal control model, where the Material Removal Rate (MRR) is comprehensively introduced, to accomplish the dynamic machining control and tool life determination of a cutting tool under an expected machining quantity. To resolve the incessant cutting-rate control problem, Calculus of Variations is implemented for the optimum solution. Additionally, the decision criteria for selecting the dynamic solution are suggested and the sensitivity analyses for key variables in the optimal solution are fully discussed. The versatility of this study is furthermore exemplified through a numerical illustration from the real-world industry with BORLAND C++ BUILDER. It is shown that the theoretical and simulated results are in good agreement. This study absolutely explores the very promising solution to dynamically organize the MRR in minimizing the machining cost of a cutting tool for the contemporary machining industry.

Multi-stage ranking of emergency technology alternatives for water source pollution accidents using a fuzzy group decision making tool.

Science.gov (United States)

Qu, Jianhua; Meng, Xianlin; You, Hong

2016-06-05

Due to the increasing number of unexpected water source pollution events, selection of the most appropriate disposal technology for a specific pollution scenario is of crucial importance to the security of urban water supplies. However, the formulation of the optimum option is considerably difficult owing to the substantial uncertainty of such accidents. In this research, a multi-stage technical screening and evaluation tool is proposed to determine the optimal technique scheme, considering the areas of pollutant elimination both in drinking water sources and water treatment plants. In stage 1, a CBR-based group decision tool was developed to screen available technologies for different scenarios. Then, the threat degree caused by the pollution was estimated in stage 2 using a threat evaluation system and was partitioned into four levels. For each threat level, a corresponding set of technique evaluation criteria weights was obtained using Group-G1. To identify the optimization alternatives corresponding to the different threat levels, an extension of TOPSIS, a multi-criteria interval-valued trapezoidal fuzzy decision making technique containing the four arrays of criteria weights, to a group decision environment was investigated in stage 3. The effectiveness of the developed tool was elaborated by two actual thallium-contaminated scenarios associated with different threat levels. Copyright © 2016 Elsevier B.V. All rights reserved.

Tools for the analysis of dose optimization: I. Effect-volume histogram

International Nuclear Information System (INIS)

Alber, M.; Nuesslin, F.

2002-01-01

With the advent of dose optimization algorithms, predominantly for intensity-modulated radiotherapy (IMRT), computer software has progressed beyond the point of being merely a tool at the hands of an expert and has become an active, independent mediator of the dosimetric conflicts between treatment goals and risks. To understand and control the internal decision finding as well as to provide means to influence it, a tool for the analysis of the dose distribution is presented which reveals the decision-making process performed by the algorithm. The internal trade-offs between partial volumes receiving high or low doses are driven by functions which attribute a weight to each volume element. The statistics of the distribution of these weights is cast into an effect-volume histogram (EVH) in analogy to dose-volume histograms. The analysis of the EVH reveals which traits of the optimum dose distribution result from the defined objectives, and which are a random consequence of under- or misspecification of treatment goals. The EVH can further assist in the process of finding suitable objectives and balancing conflicting objectives. If biologically inspired objectives are used, the EVH shows the distribution of local dose effect relative to the prescribed level. (author)

Extensions of dynamic programming as a new tool for decision tree optimization

KAUST Repository

Alkhalid, Abdulaziz; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2013-01-01

The chapter is devoted to the consideration of two types of decision trees for a given decision table: α-decision trees (the parameter α controls the accuracy of tree) and decision trees (which allow arbitrary level of accuracy). We study

An optimal hierarchical decision model for a regional logistics network with environmental impact consideration.

Science.gov (United States)

Zhang, Dezhi; Li, Shuangyan; Qin, Jin

2014-01-01

This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

Directory of Open Access Journals (Sweden)

Dezhi Zhang

2014-01-01

Full Text Available This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users’ demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators’ service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

Science.gov (United States)

Zhang, Dezhi; Li, Shuangyan

2014-01-01

This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level. PMID:24977209

Investigation of effective decision criteria for multiobjective optimization in IMRT.

Science.gov (United States)

Holdsworth, Clay; Stewart, Robert D; Kim, Minsun; Liao, Jay; Phillips, Mark H

2011-06-01

To investigate how using different sets of decision criteria impacts the quality of intensity modulated radiation therapy (IMRT) plans obtained by multiobjective optimization. A multiobjective optimization evolutionary algorithm (MOEA) was used to produce sets of IMRT plans. The MOEA consisted of two interacting algorithms: (i) a deterministic inverse planning optimization of beamlet intensities that minimizes a weighted sum of quadratic penalty objectives to generate IMRT plans and (ii) an evolutionary algorithm that selects the superior IMRT plans using decision criteria and uses those plans to determine the new weights and penalty objectives of each new plan. Plans resulting from the deterministic algorithm were evaluated by the evolutionary algorithm using a set of decision criteria for both targets and organs at risk (OARs). Decision criteria used included variation in the target dose distribution, mean dose, maximum dose, generalized equivalent uniform dose (gEUD), an equivalent uniform dose (EUD(alpha,beta) formula derived from the linear-quadratic survival model, and points on dose volume histograms (DVHs). In order to quantatively compare results from trials using different decision criteria, a neutral set of comparison metrics was used. For each set of decision criteria investigated, IMRT plans were calculated for four different cases: two simple prostate cases, one complex prostate Case, and one complex head and neck Case. When smaller numbers of decision criteria, more descriptive decision criteria, or less anti-correlated decision criteria were used to characterize plan quality during multiobjective optimization, dose to OARs and target dose variation were reduced in the final population of plans. Mean OAR dose and gEUD (a = 4) decision criteria were comparable. Using maximum dose decision criteria for OARs near targets resulted in inferior populations that focused solely on low target variance at the expense of high OAR dose. Target dose range, (D

Optimal soil venting design using Bayesian Decision analysis

OpenAIRE

Kaluarachchi, J. J.; Wijedasa, A. H.

1994-01-01

Remediation of hydrocarbon-contaminated sites can be costly and the design process becomes complex in the presence of parameter uncertainty. Classical decision theory related to remediation design requires the parameter uncertainties to be stipulated in terms of statistical estimates based on site observations. In the absence of detailed data on parameter uncertainty, classical decision theory provides little contribution in designing a risk-based optimal design strategy. Bayesian decision th...

SPOT-A SENSOR PLACEMENT OPTIMIZATION TOOL FOR ...

Science.gov (United States)

journal article This paper presents SPOT, a Sensor Placement Optimization Tool. SPOT provides a toolkit that facilitates research in sensor placement optimization and enables the practical application of sensor placement solvers to real-world CWS design applications. This paper provides an overview of SPOT’s key features, and then illustrates how this tool can be flexibly applied to solve a variety of different types of sensor placement problems.

Dynamic Programming Approach for Exact Decision Rule Optimization

KAUST Repository

Amin, Talha

2013-01-01

This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from UCI Machine Learning Repository. © Springer-Verlag Berlin Heidelberg 2013.

Optimal management of replacement heifers in a beef herd: a model for simultaneous optimization of rearing and breeding decisions.

Science.gov (United States)

Stygar, A H; Kristensen, A R; Makulska, J

2014-08-01

The aim of this study was to provide farmers an efficient tool for supporting optimal decisions in the beef heifer rearing process. The complexity of beef heifer management prompted the development of a model including decisions on the feeding level during prepuberty (age optimal rearing strategy was found by maximizing the total discounted net revenues from the predicted future productivity of the Polish Limousine heifers defined as the cumulative BW of calves born from a cow calved until the age of 5 yr, standardized on the 210th day of age. According to the modeled optimal policy, heifers fed during the whole rearing period at the ADG of 810 g/d and generally weaned after the maximum suckling period of 9 mo should already be bred at the age of 13.2 mo and BW constituting 55.6% of the average mature BW. Based on the optimal strategy, 52% of all heifers conceived from May to July and calved from February to April. This optimal rearing pattern resulted in an average net return of EUR 311.6 per pregnant heifer. It was found that the economic efficiency of beef operations can be improved by applying different herd management practices to those currently used in Poland. Breeding at 55.6% of the average mature BW, after a shorter and less expensive rearing period, resulted in an increase in the average net return per heifer by almost 18% compared to the conventional system, in which heifers were bred after attaining 65% of the mature BW. Extension of the rearing period by 2.5 mo (breeding at the age 15.7 mo), due to a prepubertal growth rate lowered by 200 g, reduced the average net return per heifer by 6.2% compared to the results obtained under the basic model assumptions. In the future, the model may also be extended to investigate additional aspects of the beef heifer development, such as the environmental impacts of various heifer management decisions.

Development of a 2nd Generation Decision Support Tool to Optimize Resource and Energy Recovery for Municipal Solid Waste

Science.gov (United States)

In 2012, EPA’s Office of Research and Development released the MSW decision support tool (MSW-DST) to help identify strategies for more sustainable MSW management. Depending upon local infrastructure, energy grid mix, population density, and waste composition and quantity, the m...

Optimization of β-decision rules relative to number of misclassifications

KAUST Repository

Zielosko, Beata

2012-01-01

In the paper, we present an algorithm for optimization of approximate decision rules relative to the number of misclassifications. The considered algorithm is based on extensions of dynamic programming and constructs a directed acyclic graph Δ β (T). Based on this graph we can describe the whole set of so-called irredundant β-decision rules. We can optimize rules from this set according to the number of misclassifications. Results of experiments with decision tables from the UCI Machine Learning Repository are presented. © 2012 Springer-Verlag.

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

Science.gov (United States)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

Promoting Shared Decision Making in Disorders of Sex Development (DSD): Decision Aids and Support Tools.

Science.gov (United States)

Siminoff, L A; Sandberg, D E

2015-05-01

Specific complaints and grievances from adult patients with disorders of sex development (DSD), and their advocates center around the lack of information or misinformation they were given about their condition and feeling stigmatized and shamed by the secrecy surrounding their condition and its management. Many also attribute poor sexual function to damaging genital surgery and/or repeated, insensitive genital examinations. These reports suggest the need to reconsider the decision-making process for the treatment of children born with DSD. This paper proposes that shared decision making, an important concept in adult health care, be operationalized for the major decisions commonly encountered in DSD care and facilitated through the utilization of decision aids and support tools. This approach may help patients and their families make informed decisions that are better aligned with their personal values and goals. It may also lead to greater confidence in decision making with greater satisfaction and less regret. A brief review of the past and current approach to DSD decision making is provided, along with a review of shared decision making and decision aids and support tools. A case study explores the need and potential utility of this suggested new approach. © Georg Thieme Verlag KG Stuttgart · New York.

Developing a Support Tool for Global Product Development Decisions

DEFF Research Database (Denmark)

Søndergaard, Erik Stefan; Ahmed-Kristensen, Saeema

2016-01-01

This paper investigates how global product development decisions are made through a multiple-case study in three Danish engineering. The paper identifies which information and methods are applied for making decisions and how decision-making can be supported based on previous experience. The paper...... presents results from 51 decisions made in the three companies, and based on the results of the studies a framework for a decision-support tool is outlined and discussed. The paper rounds off with an identification of future research opportunities in the area of global product development and decision-making....

Optimal Waste Load Allocation Using Multi-Objective Optimization and Multi-Criteria Decision Analysis

Directory of Open Access Journals (Sweden)

L. Saberi

2016-10-01

Full Text Available Introduction: Increasing demand for water, depletion of resources of acceptable quality, and excessive water pollution due to agricultural and industrial developments has caused intensive social and environmental problems all over the world. Given the environmental importance of rivers, complexity and extent of pollution factors and physical, chemical and biological processes in these systems, optimal waste-load allocation in river systems has been given considerable attention in the literature in the past decades. The overall objective of planning and quality management of river systems is to develop and implement a coordinated set of strategies and policies to reduce or allocate of pollution entering the rivers so that the water quality matches by proposing environmental standards with an acceptable reliability. In such matters, often there are several different decision makers with different utilities which lead to conflicts. Methods/Materials: In this research, a conflict resolution framework for optimal waste load allocation in river systems is proposed, considering the total treatment cost and the Biological Oxygen Demand (BOD violation characteristics. There are two decision-makers inclusive waste load discharges coalition and environmentalists who have conflicting objectives. This framework consists of an embedded river water quality simulator, which simulates the transport process including reaction kinetics. The trade-off curve between objectives is obtained using the Multi-objective Particle Swarm Optimization Algorithm which these objectives are minimization of the total cost of treatment and penalties that must be paid by discharges and a violation of water quality standards considering BOD parameter which is controlled by environmentalists. Thus, the basic policy of river’s water quality management is formulated in such a way that the decision-makers are ensured their benefits will be provided as far as possible. By using MOPSO

On algorithm for building of optimal α-decision trees

KAUST Repository

Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail

2010-01-01

The paper describes an algorithm that constructs approximate decision trees (α-decision trees), which are optimal relatively to one of the following complexity measures: depth, total path length or number of nodes. The algorithm uses dynamic

Microseismic Monitoring Design Optimization Based on Multiple Criteria Decision Analysis

Science.gov (United States)

Kovaleva, Y.; Tamimi, N.; Ostadhassan, M.

2017-12-01

Borehole microseismic monitoring of hydraulic fracture treatments of unconventional reservoirs is a widely used method in the oil and gas industry. Sometimes, the quality of the acquired microseismic data is poor. One of the reasons for poor data quality is poor survey design. We attempt to provide a comprehensive and thorough workflow, using multiple criteria decision analysis (MCDA), to optimize planning micriseismic monitoring. So far, microseismic monitoring has been used extensively as a powerful tool for determining fracture parameters that affect the influx of formation fluids into the wellbore. The factors that affect the quality of microseismic data and their final results include average distance between microseismic events and receivers, complexity of the recorded wavefield, signal-to-noise ratio, data aperture, etc. These criteria often conflict with each other. In a typical microseismic monitoring, those factors should be considered to choose the best monitoring well(s), optimum number of required geophones, and their depth. We use MDCA to address these design challenges and develop a method that offers an optimized design out of all possible combinations to produce the best data acquisition results. We believe that this will be the first research to include the above-mentioned factors in a 3D model. Such a tool would assist companies and practicing engineers in choosing the best design parameters for future microseismic projects.

Integrating LCA and Risk Assessment for Decision Support

DEFF Research Database (Denmark)

Dong, Yan; Miraglia, Simona; Manzo, Stefano

The study aims at developing a methodology using decision analysis theory and tools to find the optimal policy (or design) of the studied system, to ensure both sustainability and meanwhile manage risks.......The study aims at developing a methodology using decision analysis theory and tools to find the optimal policy (or design) of the studied system, to ensure both sustainability and meanwhile manage risks....

Rade-aid: an operational tool for decision-makers

International Nuclear Information System (INIS)

Wagenaar, G.; van den Bosch, C.J.H.; Ehrhardt, J.; Steinhauer, C.; Morrey, M.; Robinson, C.A.

1991-01-01

If an accidental release of radionuclides occurs, decisions on countermeasures are required. Since the making of a decision involves many competing factors (for instance, the health risk versus the costs relating to a countermeasure), the decision-maker faces a problem. The aim of the RADE-AID (Radiological Accident DEcision AIDing) project is the development of a computer decision support system which can be used in the formulation of decisions. The theoretical background of the decision technique and its methods are outlined, together with the practical application of the technique in the form of the software package developed. Both the benefits of formal techniques and computerized tools in this field are discussed. In order to explore the appropriateness of the decision technique for the management of radiological emergencies, illustrative, but stylized, applications were carried out. Conclusions from these applications are discussed

Decision-Making Tool for Cost-Efficient and Environmentally Friendly Wood Mobilisation

Directory of Open Access Journals (Sweden)

Matevž Triplat

2015-06-01

Full Text Available Background and Purpose: With development of forest management technologies, the efficiency of wood production was significantly improved, and thus the impact on forests has changed as well. The article presents a practical decision-making tool for selection of most suitable harvesting system, considering given terrain as well as expected soil conditions on harvesting sites. The decision-making tool should support cost-efficient and environmentally friendly mobilisation of wood. Materials and Methods: The presented decision-making tool is based on ground bearing capacities (relevant environmental parameter and nominal ground pressure (harvesting system characteristics. Soil and terrain (slope characteristics were taken into account for selection of the most suitable harvesting system. Three-step methodological approach was suggested, where soil and terrain conditions were defined in first step, while harvesting system were described using wood process charts (“functiogramms” in second step. In final step ecological and technological requirements were matched. Results: To exemplify the three-step methodology, a decision-making tool was prepared for the three selected harvesting systems. The proposed harvesting systems differ in technological, ecological and economic aspects, but each is limited by at least one of the aspect. Conclusions: The decision-making tool in combination with the presented wood process charts (“functiogramms” can simplify and facilitate forest production planning, although it can also be used in case of unforeseen event e.g. changing of soil moisture, machinery failure and insufficient current capacities. Considering the envisaged quantities and types of forest wooden assortments, it is possible to use the decision-making tool for a basic selection of most appropriate harvesting systems. The main idea behind the suggested three step methodological approach is that forest workers can prepare individual decision

Development of transportation asset management decision support tools : final report.

Science.gov (United States)

2017-08-09

This study developed a web-based prototype decision support platform to demonstrate the benefits of transportation asset management in monitoring asset performance, supporting asset funding decisions, planning budget tradeoffs, and optimizing resourc...

Clinical Decision Support Tools: The Evolution of a Revolution

NARCIS (Netherlands)

Mould, D. R.; D'Haens, G.; Upton, R. N.

2016-01-01

Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug

BUSINESS INTELLIGENCE TOOLS FOR DATA ANALYSIS AND DECISION MAKING

Directory of Open Access Journals (Sweden)

DEJAN ZDRAVESKI

2011-04-01

Full Text Available Every business is dynamic in nature and is affected by various external and internal factors. These factors include external market conditions, competitors, internal restructuring and re-alignment, operational optimization and paradigm shifts in the business itself. New regulations and restrictions, in combination with the above factors, contribute to the constant evolutionary nature of compelling, business-critical information; the kind of information that an organization needs to sustain and thrive. Business intelligence (“BI” is broad term that encapsulates the process of gathering information pertaining to a business and the market it functions in. This information when collated and analyzed in the right manner, can provide vital insights into the business and can be a tool to improve efficiency, reduce costs, reduce time lags and bring many positive changes. A business intelligence application helps to achieve precisely that. Successful organizations maximize the use of their data assets through business intelligence technology. The first data warehousing and decision support tools introduced companies to the power and benefits of accessing and analyzing their corporate data. Business users at every level found new, more sophisticated ways to analyze and report on the information mined from their vast data warehouses.Choosing a Business Intelligence offering is an important decision for an enterprise, one that will have a significant impact throughout the enterprise. The choice of a BI offering will affect people up and down the chain of command (senior management, analysts, and line managers and across functional areas (sales, finance, and operations. It will affect business users, application developers, and IT professionals. BI applications include the activities of decision support systems (DSS, query and reporting, online analyticalprocessing (OLAP, statistical analysis, forecasting, and data mining. Another way of phrasing this is

ToTem: a tool for variant calling pipeline optimization.

Science.gov (United States)

Tom, Nikola; Tom, Ondrej; Malcikova, Jitka; Pavlova, Sarka; Kubesova, Blanka; Rausch, Tobias; Kolarik, Miroslav; Benes, Vladimir; Bystry, Vojtech; Pospisilova, Sarka

2018-06-26

High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. ToTem is a tool for automated pipeline optimization which is freely available as a web application at  https://totem.software .

On developing a prospecting tool for wind industry and policy decision support

International Nuclear Information System (INIS)

McKeown, Charles; Adelaja, Adesoji; Calnin, Benjamin

2011-01-01

This paper presents the rudiments of a Wind Prospecting Tool designed to inform private and public decision makers involved in wind industry development in reducing transaction costs associated with identifying areas of mutual focus within a state. The multiple layer decision support framework has proven to be valuable to industry, state government and local decision makers. Information on wind resources, land availability, potential land costs, potential NIMBYism concerns and economic development potential were integrated to develop a framework for decision support. The paper also highlights implications for decision support research and the role of higher education in providing anticipatory science to enhance private and public choices in economic development. - Research Highlights: →In this paper we explore the building and value of a wind industry location decision support tool. →We examine the development process from the industry perspective. →We discuss the creation of a decision support tool that was designed for industry, state policy makers and local decision makers. →We build a model framework for wind prospecting decision support. →Finally we discuss the impact on local and state decision making as a result of being informed by science based decision support.

Algorithms for optimal dyadic decision trees

Energy Technology Data Exchange (ETDEWEB)

Hush, Don [Los Alamos National Laboratory; Porter, Reid [Los Alamos National Laboratory

2009-01-01

A new algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data sets. This paper enhances and extends this algorithm by: introducing an adaptive grid search for the regularization parameter that guarantees optimal solutions for all relevant trees sizes, revising the core tree-building algorithm so that its run time is substantially smaller for most regularization parameter values on the grid, and incorporating new data structures and data pre-processing steps that provide significant run time enhancement in practice.

For Third Enrollment Period, Marketplaces Expand Decision Support Tools To Assist Consumers.

Science.gov (United States)

Wong, Charlene A; Polsky, Daniel E; Jones, Arthur T; Weiner, Janet; Town, Robert J; Baker, Tom

2016-04-01

The design of the Affordable Care Act's online health insurance Marketplaces can improve how consumers make complex health plan choices. We examined the choice environment on the state-based Marketplaces and HealthCare.gov in the third open enrollment period. Compared to previous enrollment periods, we found greater adoption of some decision support tools, such as total cost estimators and integrated provider lookups. Total cost estimators differed in how they generated estimates: In some Marketplaces, consumers categorized their own utilization, while in others, consumers answered detailed questions and were assigned a utilization profile. The tools available before creating an account (in the window-shopping period) and afterward (in the real-shopping period) differed in several Marketplaces. For example, five Marketplaces provided total cost estimators to window shoppers, but only two provided them to real shoppers. Further research is needed on the impact of different choice environments and on which tools are most effective in helping consumers pick optimal plans. Project HOPE—The People-to-People Health Foundation, Inc.

Optimization of approximate decision rules relative to number of misclassifications

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2012-01-01

In the paper, we study an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the number of misclassifications. We introduce an uncertainty measure J(T) which is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. The presented algorithm constructs a directed acyclic graph Δγ(T). Based on this graph we can describe the whole set of so-called irredundant γ-decision rules. We can optimize rules from this set according to the number of misclassifications. Results of experiments with decision tables from the UCI Machine Learning Repository are presented. © 2012 The authors and IOS Press. All rights reserved.

Optimization of approximate decision rules relative to number of misclassifications

KAUST Repository

Amin, Talha

2012-12-01

In the paper, we study an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the number of misclassifications. We introduce an uncertainty measure J(T) which is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. The presented algorithm constructs a directed acyclic graph Δγ(T). Based on this graph we can describe the whole set of so-called irredundant γ-decision rules. We can optimize rules from this set according to the number of misclassifications. Results of experiments with decision tables from the UCI Machine Learning Repository are presented. © 2012 The authors and IOS Press. All rights reserved.

People adopt optimal policies in simple decision-making, after practice and guidance.

Science.gov (United States)

Evans, Nathan J; Brown, Scott D

2017-04-01

Organisms making repeated simple decisions are faced with a tradeoff between urgent and cautious strategies. While animals can adopt a statistically optimal policy for this tradeoff, findings about human decision-makers have been mixed. Some studies have shown that people can optimize this "speed-accuracy tradeoff", while others have identified a systematic bias towards excessive caution. These issues have driven theoretical development and spurred debate about the nature of human decision-making. We investigated a potential resolution to the debate, based on two factors that routinely differ between human and animal studies of decision-making: the effects of practice, and of longer-term feedback. Our study replicated the finding that most people, by default, are overly cautious. When given both practice and detailed feedback, people moved rapidly towards the optimal policy, with many participants reaching optimality with less than 1 h of practice. Our findings have theoretical implications for cognitive and neural models of simple decision-making, as well as methodological implications.

ERDOS 1.0. Emergency response decisions as problems of optimal stopping

International Nuclear Information System (INIS)

Pauwels, N.

1998-11-01

The ERDOS-software is a stochastic dynamic program to support the decision problem of preventively evacuating the workers of an industrial company threatened by a nuclear accident taking place in the near future with a particular probability. ERDOS treats this problem as one of optimal stopping: the governmental decision maker initially holds a call option enabling him to postpone the evacuation decision and observe the further evolution of the alarm situation. As such, he has to decide on the optimal point in time to exercise this option, i.e. to take the irreversible decision to evacuate the threatened workers. ERDOS allows to calculate the expected costs of an optimal intervention strategy and to compare this outcome with the costs resulting from a myopic evacuation decision, ignoring the prospect of more complete information at later stages of the decision process. Furthermore, ERDOS determines the free boundary, giving the critical severity as a function of time that will trigger immediate evacuation in case it is exceeded. Finally, the software provides useful insights in the financial implications of loosing time during the initial stages of the decision process (due to the gathering of information, discussions on the intervention strategy and so on)

Heuristic and optimal policy computations in the human brain during sequential decision-making.

Science.gov (United States)

Korn, Christoph W; Bach, Dominik R

2018-01-23

Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

Measuring and monitoring energy access: Decision-support tools for policymakers in Africa

International Nuclear Information System (INIS)

Hailu, Yohannes G.

2012-01-01

A significant number of African States have adapted energy access targets. In evaluating progress towards these goals, measuring and monitoring energy access becomes relevant. This paper reviews energy access indicators and identifies their utility and challenges in their application. By focusing on Africa, a broader framework for energy access measurement and monitoring is discussed, along with implementation barriers and potential solutions. To demonstrate the utility of energy access decision-support tool in Africa, a scenario analysis in five regional energy pools is conducted using the Energy Spending Model tool. Institutionalizing monitoring and decision-support tools can provide valuable feedback to policymakers aiming to design and implement effective energy access programs serving a growing population in Africa. - Highlights: ► Most African countries have adapted energy access targets. ► To monitor and evaluate performance, monitoring and decision-support tools are required. ► Framework for tool development should consider data, cost, political and other factors. ► Implementation constraints include technical, data, resource and urban/rural issues. ► Electricity Spending Needs model is one decision support tool that ties access targets to investment needs. ► Monitoring tools provide crucial feedback on Africa's energy access progress.

Gaps in tools assessing the energy implications of renovation versus rebuilding decisions

DEFF Research Database (Denmark)

Goldstein, Benjamin Paul; Herbøl, Mads; Meza, Maria Josefina Figueroa

2013-01-01

to evaluate project level energy-related decisions than at larger scales. Information gaps identified within assessment tools lead to uncertainty for decision makers about which option improves energy efficiency. In the case of a number of large-scale EU building renovating/renewing projects these tools have......The state of building stocks changes over time. Owners and municipalities face the choice to renovate or rebuild buildings to improve energy efficiency. This review addresses how current sustainability assessment tools support these decisions. It finds that advanced tools are better tailored...... been scarcely used or merely suggested during planning. Recent advances in sustainability assessment tools can begin to close some of the existing knowledge gaps, while incentives and stricter legislation may improve their usage rates....

Decision optimization of case-based computer-aided decision systems using genetic algorithms with application to mammography

International Nuclear Information System (INIS)

Mazurowski, Maciej A; Habas, Piotr A; Zurada, Jacek M; Tourassi, Georgia D

2008-01-01

This paper presents an optimization framework for improving case-based computer-aided decision (CB-CAD) systems. The underlying hypothesis of the study is that each example in the knowledge database of a medical decision support system has different importance in the decision making process. A new decision algorithm incorporating an importance weight for each example is proposed to account for these differences. The search for the best set of importance weights is defined as an optimization problem and a genetic algorithm is employed to solve it. The optimization process is tailored to maximize the system's performance according to clinically relevant evaluation criteria. The study was performed using a CAD system developed for the classification of regions of interests (ROIs) in mammograms as depicting masses or normal tissue. The system was constructed and evaluated using a dataset of ROIs extracted from the Digital Database for Screening Mammography (DDSM). Experimental results show that, according to receiver operator characteristic (ROC) analysis, the proposed method significantly improves the overall performance of the CAD system as well as its average specificity for high breast mass detection rates

Demonstration of Decision Support Tools for Sustainable Development

Energy Technology Data Exchange (ETDEWEB)

Shropshire, David Earl; Jacobson, Jacob Jordan; Berrett, Sharon; Cobb, D. A.; Worhach, P.

2000-11-01

The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.

GMOseek: a user friendly tool for optimized GMO testing.

Science.gov (United States)

Morisset, Dany; Novak, Petra Kralj; Zupanič, Darko; Gruden, Kristina; Lavrač, Nada; Žel, Jana

2014-08-01

With the increasing pace of new Genetically Modified Organisms (GMOs) authorized or in pipeline for commercialization worldwide, the task of the laboratories in charge to test the compliance of food, feed or seed samples with their relevant regulations became difficult and costly. Many of them have already adopted the so called "matrix approach" to rationalize the resources and efforts used to increase their efficiency within a limited budget. Most of the time, the "matrix approach" is implemented using limited information and some proprietary (if any) computational tool to efficiently use the available data. The developed GMOseek software is designed to support decision making in all the phases of routine GMO laboratory testing, including the interpretation of wet-lab results. The tool makes use of a tabulated matrix of GM events and their genetic elements, of the laboratory analysis history and the available information about the sample at hand. The tool uses an optimization approach to suggest the most suited screening assays for the given sample. The practical GMOseek user interface allows the user to customize the search for a cost-efficient combination of screening assays to be employed on a given sample. It further guides the user to select appropriate analyses to determine the presence of individual GM events in the analyzed sample, and it helps taking a final decision regarding the GMO composition in the sample. GMOseek can also be used to evaluate new, previously unused GMO screening targets and to estimate the profitability of developing new GMO screening methods. The presented freely available software tool offers the GMO testing laboratories the possibility to select combinations of assays (e.g. quantitative real-time PCR tests) needed for their task, by allowing the expert to express his/her preferences in terms of multiplexing and cost. The utility of GMOseek is exemplified by analyzing selected food, feed and seed samples from a national reference

Practical Application of Modern Forecasting and Decision Tools at an Operational River Management Agency

Science.gov (United States)

Jawdy, C. M.; Carney, S.; Barber, N. M.; Balk, B. C.; Miller, G. A.

2017-12-01

The Tennessee Valley Authority (TVA) recently completed a complete overhaul of our River Forecast System (RFS). This modernization effort encompassed: uplift or addition of 89 data feeds calibration of a 140 subbasin rainfall-runoff model calibration of over 650 miles of hydraulic routings implementation of a decision optimization routine for 29 reservoirs implementation of hydrothermal forecast models for five river-cooled thermal plants creation of decision-friendly displays creation of a user-friendly wiki creation of a robust reporting system This talk will walk attendees through how a 24x7 river and grid management agency made decisions around how to operationalize the latest technologies in hydrology, hydraulics, decision science and information technology. The tradeoffs inherent in such an endeavor will be discussed so that research-oriented attendees can understand how best to align their research if they desire adoption within industry. More industry-oriented attendees can learn about the mechanics of how to succeed at such a large and complex project. Following the description of the modernization project, I can discuss TVA's plans for future growth of the system. We plan to add the following capabilities in the coming years: forecast verification tools to communicate floodplain risk tools to choose the best possible model forcings ensemble inflow modelling a river policy that allows for more reasonable tradeoff of benefits river decisions based on ensembles The iterative staging of such improvements is highly fraught with technical, political and operational risks. I will discuss how TVA's is using what we learned in the RFS modernization effort to grow further into delivering on the promise of these additional technologies.

A Gaussian decision-support tool for engineering design process

NARCIS (Netherlands)

Rajabali Nejad, Mohammadreza; Spitas, Christos

2013-01-01

Decision-making in design is of great importance, resulting in success or failure of a system (Liu et al., 2010; Roozenburg and Eekels, 1995; Spitas, 2011a). This paper describes a robust decision-support tool for engineering design process, which can be used throughout the design process in either

Automated Multivariate Optimization Tool for Energy Analysis: Preprint

Energy Technology Data Exchange (ETDEWEB)

Ellis, P. G.; Griffith, B. T.; Long, N.; Torcellini, P. A.; Crawley, D.

2006-07-01

Building energy simulations are often used for trial-and-error evaluation of ''what-if'' options in building design--a limited search for an optimal solution, or ''optimization''. Computerized searching has the potential to automate the input and output, evaluate many options, and perform enough simulations to account for the complex interactions among combinations of options. This paper describes ongoing efforts to develop such a tool. The optimization tool employs multiple modules, including a graphical user interface, a database, a preprocessor, the EnergyPlus simulation engine, an optimization engine, and a simulation run manager. Each module is described and the overall application architecture is summarized.

Decision and Inhibitory Trees for Decision Tables with Many-Valued Decisions

KAUST Repository

Azad, Mohammad

2018-06-06

Decision trees are one of the most commonly used tools in decision analysis, knowledge representation, machine learning, etc., for its simplicity and interpretability. We consider an extension of dynamic programming approach to process the whole set of decision trees for the given decision table which was previously only attainable by brute-force algorithms. We study decision tables with many-valued decisions (each row may contain multiple decisions) because they are more reasonable models of data in many cases. To address this problem in a broad sense, we consider not only decision trees but also inhibitory trees where terminal nodes are labeled with “̸= decision”. Inhibitory trees can sometimes describe more knowledge from datasets than decision trees. As for cost functions, we consider depth or average depth to minimize time complexity of trees, and the number of nodes or the number of the terminal, or nonterminal nodes to minimize the space complexity of trees. We investigate the multi-stage optimization of trees relative to some cost functions, and also the possibility to describe the whole set of strictly optimal trees. Furthermore, we study the bi-criteria optimization cost vs. cost and cost vs. uncertainty for decision trees, and cost vs. cost and cost vs. completeness for inhibitory trees. The most interesting application of the developed technique is the creation of multi-pruning and restricted multi-pruning approaches which are useful for knowledge representation and prediction. The experimental results show that decision trees constructed by these approaches can often outperform the decision trees constructed by the CART algorithm. Another application includes the comparison of 12 greedy heuristics for single- and bi-criteria optimization (cost vs. cost) of trees. We also study the three approaches (decision tables with many-valued decisions, decision tables with most common decisions, and decision tables with generalized decisions) to handle

The impact of chief executive officer optimism on hospital strategic decision making.

Science.gov (United States)

Langabeer, James R; Yao, Emery

2012-01-01

Previous strategic decision making research has focused mostly on the analytical positioning approach, which broadly emphasizes an alignment between rationality and the external environment. In this study, we propose that hospital chief executive optimism (or the general tendency to expect positive future outcomes) will moderate the relationship between comprehensively rational decision-making process and organizational performance. The purpose of this study was to explore the impact that dispositional optimism has on the well-established relationship between rational decision-making processes and organizational performance. Specifically, we hypothesized that optimism will moderate the relationship between the level of rationality and the organization's performance. We further suggest that this relationship will be more negative for those with high, as opposed to low, optimism. We surveyed 168 hospital CEOs and used moderated hierarchical regression methods to statically test our hypothesis. On the basis of a survey study of 168 hospital CEOs, we found evidence of a complex interplay of optimism in the rationality-organizational performance relationship. More specifically, we found that the two-way interactions between optimism and rational decision making were negatively associated with performance and that where optimism was the highest, the rationality-performance relationship was the most negative. Executive optimism was positively associated with organizational performance. We also found that greater perceived environmental turbulence, when interacting with optimism, did not have a significant interaction effect on the rationality-performance relationship. These findings suggest potential for broader participation in strategic processes and the use of organizational development techniques that assess executive disposition and traits for recruitment processes, because CEO optimism influences hospital-level processes. Research implications include incorporating

FRAMEWORK FOR ENVIRONMENTAL DECISION-MAKING, FRED: A TOOL FOR ENVIRONMENTALLY-PREFERABLE PURCHASING

Science.gov (United States)

In support of the Environmentally Preferable Purchasing Program of the US EPA, the Systems Analysis Branch has developed a decision-making tool based on life cycle assessment. This tool, the Framework for Responsible Environmental Decision-making or FRED streamlines LCA by choosi...

Bayesian emulation for optimization in multi-step portfolio decisions

OpenAIRE

Irie, Kaoru; West, Mike

2016-01-01

We discuss the Bayesian emulation approach to computational solution of multi-step portfolio studies in financial time series. "Bayesian emulation for decisions" involves mapping the technical structure of a decision analysis problem to that of Bayesian inference in a purely synthetic "emulating" statistical model. This provides access to standard posterior analytic, simulation and optimization methods that yield indirect solutions of the decision problem. We develop this in time series portf...

A free software tool for the development of decision support systems

Directory of Open Access Journals (Sweden)

COLONESE, G

2008-06-01

Full Text Available This article describes PostGeoOlap, a free software open source tool for decision support that integrates OLAP (On-Line Analytical Processing and GIS (Geographical Information Systems. Besides describing the tool, we show how it can be used to achieve effective and low cost decision support that is adequate for small and medium companies and for small public offices.

Integrated environmental decision support tool based on GIS technology

International Nuclear Information System (INIS)

Doctor, P.G.; O'Neil, T.K.; Sackschewsky, M.R.; Becker, J.M.; Rykiel, E.J.; Walters, T.B.; Brandt, C.A.; Hall, J.A.

1995-01-01

Environmental restoration and management decisions facing the US Department of Energy require balancing trade-offs between diverse land uses and impacts over multiple spatial and temporal scales. Many types of environmental data have been collected for the Hanford Site and the Columbia River in Washington State over the past fifty years. Pacific Northwest National Laboratory (PNNL) is integrating these data into a Geographic Information System (GIS) based computer decision support tool. This tool provides a comprehensive and concise description of the current environmental landscape that can be used to evaluate the ecological and monetary trade-offs between future land use, restoration and remediation options before action is taken. Ecological impacts evaluated include effects to individual species of concern and habitat loss and fragmentation. Monetary impacts include those associated with habitat mitigation. The tool is organized as both a browsing tool for educational purposes, and as a framework that leads a project manager through the steps needed to be in compliance with environmental requirements

A Monte Carlo based decision-support tool for assessing generation portfolios in future carbon constrained electricity industries

International Nuclear Information System (INIS)

Vithayasrichareon, Peerapat; MacGill, Iain F.

2012-01-01

This paper presents a novel decision-support tool for assessing future generation portfolios in an increasingly uncertain electricity industry. The tool combines optimal generation mix concepts with Monte Carlo simulation and portfolio analysis techniques to determine expected overall industry costs, associated cost uncertainty, and expected CO 2 emissions for different generation portfolio mixes. The tool can incorporate complex and correlated probability distributions for estimated future fossil-fuel costs, carbon prices, plant investment costs, and demand, including price elasticity impacts. The intent of this tool is to facilitate risk-weighted generation investment and associated policy decision-making given uncertainties facing the electricity industry. Applications of this tool are demonstrated through a case study of an electricity industry with coal, CCGT, and OCGT facing future uncertainties. Results highlight some significant generation investment challenges, including the impacts of uncertain and correlated carbon and fossil-fuel prices, the role of future demand changes in response to electricity prices, and the impact of construction cost uncertainties on capital intensive generation. The tool can incorporate virtually any type of input probability distribution, and support sophisticated risk assessments of different portfolios, including downside economic risks. It can also assess portfolios against multi-criterion objectives such as greenhouse emissions as well as overall industry costs. - Highlights: ► Present a decision support tool to assist generation investment and policy making under uncertainty. ► Generation portfolios are assessed based on their expected costs, risks, and CO 2 emissions. ► There is tradeoff among expected cost, risks, and CO 2 emissions of generation portfolios. ► Investment challenges include economic impact of uncertainties and the effect of price elasticity. ► CO 2 emissions reduction depends on the mix of

Shared decision making in type 2 diabetes with a support decision tool that takes into account clinical factors, the intensity of treatment and patient preferences : Design of a cluster randomised (OPTIMAL) trial

NARCIS (Netherlands)

Den Ouden, Henk; Vos, Rimke C.; Reidsma, Carla; Rutten, Guy Ehm

2015-01-01

Background: No more than 10-15% of type 2 diabetes mellitus (T2DM) patients achieve all treatment goals regarding glycaemic control, lipids and blood pressure. Shared decision making (SDM) should increase that percentage; however, not all support decision tools are appropriate. Because the

Optimizing Engineering Tools Using Modern Ground Architectures

Science.gov (United States)

2017-12-01

ENGINEERING TOOLS USING MODERN GROUND ARCHITECTURES by Ryan P. McArdle December 2017 Thesis Advisor: Marc Peters Co-Advisor: I.M. Ross...Master’s thesis 4. TITLE AND SUBTITLE OPTIMIZING ENGINEERING TOOLS USING MODERN GROUND ARCHITECTURES 5. FUNDING NUMBERS 6. AUTHOR(S) Ryan P. McArdle 7... engineering tools. First, the effectiveness of MathWorks’ Parallel Computing Toolkit is assessed when performing somewhat basic computations in

Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

International Nuclear Information System (INIS)

Dong, Feifei; Liu, Yong; Su, Han; Zou, Rui; Guo, Huaicheng

2015-01-01

Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

Energy Technology Data Exchange (ETDEWEB)

Dong, Feifei [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Liu, Yong, E-mail: yongliu@pku.edu.cn [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Institute of Water Sciences, Peking University, Beijing 100871 (China); Su, Han [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Zou, Rui [Tetra Tech, Inc., 10306 Eaton Place, Ste 340, Fairfax, VA 22030 (United States); Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Kunming 650034 (China); Guo, Huaicheng [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China)

2015-05-15

Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

A Branch-and-Price approach to find optimal decision trees

NARCIS (Netherlands)

Firat, M.; Crognier, Guillaume; Gabor, Adriana; Zhang, Y.

2018-01-01

In Artificial Intelligence (AI) field, decision trees have gained certain importance due to their effectiveness in solving classification and regression problems. Recently, in the literature we see finding optimal decision trees are formulated as Mixed Integer Linear Programming (MILP) models. This

Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach

Directory of Open Access Journals (Sweden)

Tomás de Jesús Mateo Sanguino

2018-01-01

Full Text Available Communication infrastructure planning is a critical design task that typically requires handling complex concepts on networking aimed at optimizing performance and resources, thus demanding high analytical and problem-solving skills to engineers. To reduce this gap, this paper describes an optimization algorithm—based on evolutionary strategy—created as an aid for decision-making prior to the real deployment of wireless LANs. The developed algorithm allows automating the design process, traditionally handmade by network technicians, in order to save time and cost by improving the WLAN arrangement. To this end, we implemented a multiobjective genetic algorithm (MOGA with the purpose of meeting two simultaneous design objectives, namely, to minimize the number of APs while maximizing the coverage signal over a whole planning area. Such approach provides efficient and scalable solutions closer to the best network design, so that we integrated the developed algorithm into an engineering tool with the goal of modelling the behavior of WLANs in ICT infrastructures. Called WiFiSim, it allows the investigation of various complex issues concerning the design of IEEE 802.11-based WLANs, thereby facilitating design of the study and design and optimal deployment of wireless LANs through complete modelling software. As a result, we comparatively evaluated three target applications considering small, medium, and large scenarios with a previous approach developed, a monoobjective genetic algorithm.

Decision-Making Tools and Their Influence on Caseworkers' Room for Discretion

DEFF Research Database (Denmark)

Høybye-Mortensen, Line Matilde

2015-01-01

One of the cornerstones in the provision of social services in modern welfare states is decision making about who is eligible for particular services or benefits. Here, the central decision maker is the caseworker who assesses clients’ needs and obligations. In response to concerns regarding...... of thirty group interviews with caseworkers. Even though all of the tools are in the shape of a form that is to be filled in, differences are found across decision-making tools. For instance, it seems as though forms based on a theoretical foundation have greater impact on caseworkers’ room for discretion...

Using multi-criteria decision making for selection of the optimal strategy for municipal solid waste management.

Science.gov (United States)

Jovanovic, Sasa; Savic, Slobodan; Jovicic, Nebojsa; Boskovic, Goran; Djordjevic, Zorica

2016-09-01

Multi-criteria decision making (MCDM) is a relatively new tool for decision makers who deal with numerous and often contradictory factors during their decision making process. This paper presents a procedure to choose the optimal municipal solid waste (MSW) management system for the area of the city of Kragujevac (Republic of Serbia) based on the MCDM method. Two methods of multiple attribute decision making, i.e. SAW (simple additive weighting method) and TOPSIS (technique for order preference by similarity to ideal solution), respectively, were used to compare the proposed waste management strategies (WMS). Each of the created strategies was simulated using the software package IWM2. Total values for eight chosen parameters were calculated for all the strategies. Contribution of each of the six waste treatment options was valorized. The SAW analysis was used to obtain the sum characteristics for all the waste management treatment strategies and they were ranked accordingly. The TOPSIS method was used to calculate the relative closeness factors to the ideal solution for all the alternatives. Then, the proposed strategies were ranked in form of tables and diagrams obtained based on both MCDM methods. As shown in this paper, the results were in good agreement, which additionally confirmed and facilitated the choice of the optimal MSW management strategy. © The Author(s) 2016.

Decision analysis to define the optimal management of athletes with anomalous aortic origin of a coronary artery.

Science.gov (United States)

Mery, Carlos M; Lopez, Keila N; Molossi, Silvana; Sexson-Tejtel, S Kristen; Krishnamurthy, Rajesh; McKenzie, E Dean; Fraser, Charles D; Cantor, Scott B

2016-11-01

The goal of this study was to use decision analysis to evaluate the impact of varying uncertainties on the outcomes of patients with anomalous aortic origin of a coronary artery. Two separate decision analysis models were created: one for anomalous left coronary artery (ALCA) and one for anomalous right coronary artery (ARCA). Three strategies were compared: observation, exercise restriction, and surgery. Probabilities and health utilities were estimated on the basis of existing literature. Deterministic and probabilistic sensitivity analyses were performed. Surgery was the optimal management strategy for patients management in anomalous aortic origin of a coronary artery depends on multiple factors, including individual patient characteristics. Decision analysis provides a tool to understand how these characteristics affect the outcomes with each management strategy and thus may aid in the decision making process for a particular patient. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Decision-Making Tool for Cost-Efficient and Environmentally Friendly Wood Mobilisation

OpenAIRE

Matevž Triplat; Peter Prislan; Nike Krajnc

2015-01-01

Background and Purpose: With development of forest management technologies, the efficiency of wood production was significantly improved, and thus the impact on forests has changed as well. The article presents a practical decision-making tool for selection of most suitable harvesting system, considering given terrain as well as expected soil conditions on harvesting sites. The decision-making tool should support cost-efficient and environmentally friendly mobilisation of wood. Materials a...

Comparison of heuristic optimization techniques for the enrichment and gadolinia distribution in BWR fuel lattices and decision analysis

International Nuclear Information System (INIS)

Castillo, Alejandro; Martín-del-Campo, Cecilia; Montes-Tadeo, José-Luis; François, Juan-Luis; Ortiz-Servin, Juan-José; Perusquía-del-Cueto, Raúl

2014-01-01

Highlights: • Different metaheuristic optimization techniques were compared. • The optimal enrichment and gadolinia distribution in a BWR fuel lattice was studied. • A decision making tool based on the Position Vector of Minimum Regret was applied. • Similar results were found for the different optimization techniques. - Abstract: In the present study a comparison of the performance of five heuristic techniques for optimization of combinatorial problems is shown. The techniques are: Ant Colony System, Artificial Neural Networks, Genetic Algorithms, Greedy Search and a hybrid of Path Relinking and Scatter Search. They were applied to obtain an “optimal” enrichment and gadolinia distribution in a fuel lattice of a boiling water reactor. All techniques used the same objective function for qualifying the different distributions created during the optimization process as well as the same initial conditions and restrictions. The parameters included in the objective function are the k-infinite multiplication factor, the maximum local power peaking factor, the average enrichment and the average gadolinia concentration of the lattice. The CASMO-4 code was used to obtain the neutronic parameters. The criteria for qualifying the optimization techniques include also the evaluation of the best lattice with burnup and the number of evaluations of the objective function needed to obtain the best solution. In conclusion all techniques obtain similar results, but there are methods that found better solutions faster than others. A decision analysis tool based on the Position Vector of Minimum Regret was applied to aggregate the criteria in order to rank the solutions according to three functions: neutronic grade at 0 burnup, neutronic grade with burnup and global cost which aggregates the computing time in the decision. According to the results Greedy Search found the best lattice in terms of the neutronic grade at 0 burnup and also with burnup. However, Greedy Search is

Evaluating online diagnostic decision support tools for the clinical setting.

Science.gov (United States)

Pryor, Marie; White, David; Potter, Bronwyn; Traill, Roger

2012-01-01

Clinical decision support tools available at the point of care are an effective adjunct to support clinicians to make clinical decisions and improve patient outcomes. We developed a methodology and applied it to evaluate commercially available online clinical diagnostic decision support (DDS) tools for use at the point of care. We identified 11 commercially available DDS tools and assessed these against an evaluation instrument that included 6 categories; general information, content, quality control, search, clinical results and other features. We developed diagnostically challenging clinical case scenarios based on real patient experience that were commonly missed by junior medical staff. The evaluation was divided into 2 phases; an initial evaluation of all identified and accessible DDS tools conducted by the Clinical Information Access Portal (CIAP) team and a second phase that further assessed the top 3 tools identified in the initial evaluation phase. An evaluation panel consisting of senior and junior medical clinicians from NSW Health conducted the second phase. Of the eleven tools that were assessed against the evaluation instrument only 4 tools completely met the DDS definition that was adopted for this evaluation and were able to produce a differential diagnosis. From the initial phase of the evaluation 4 DDS tools scored 70% or more (maximum score 96%) for the content category, 8 tools scored 65% or more (maximum 100%) for the quality control category, 5 tools scored 65% or more (maximum 94%) for the search category, and 4 tools score 70% or more (maximum 81%) for the clinical results category. The second phase of the evaluation was focused on assessing diagnostic accuracy for the top 3 tools identified in the initial phase. Best Practice ranked highest overall against the 6 clinical case scenarios used. Overall the differentiating factor between the top 3 DDS tools was determined by diagnostic accuracy ranking, ease of use and the confidence and

Optimal decisions principles of programming

CERN Document Server

Lange, Oskar

1971-01-01

Optimal Decisions: Principles of Programming deals with all important problems related to programming.This book provides a general interpretation of the theory of programming based on the application of the Lagrange multipliers, followed by a presentation of the marginal and linear programming as special cases of this general theory. The praxeological interpretation of the method of Lagrange multipliers is also discussed.This text covers the Koopmans' model of transportation, geometric interpretation of the programming problem, and nature of activity analysis. The solution of t

Optimal Selection of Clustering Algorithm via Multi-Criteria Decision Analysis (MCDA for Load Profiling Applications

Directory of Open Access Journals (Sweden)

Ioannis P. Panapakidis

2018-02-01

Full Text Available Due to high implementation rates of smart meter systems, considerable amount of research is placed in machine learning tools for data handling and information retrieval. A key tool in load data processing is clustering. In recent years, a number of researches have proposed different clustering algorithms in the load profiling field. The present paper provides a methodology for addressing the aforementioned problem through Multi-Criteria Decision Analysis (MCDA and namely, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS. A comparison of the algorithms is employed. Next, a single test case on the selection of an algorithm is examined. User specific weights are applied and based on these weight values, the optimal algorithm is drawn.

Data Mining and Optimization Tools for Developing Engine Parameters Tools

Science.gov (United States)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Weather Avoidance Using Route Optimization as a Decision Aid: An AWIN Topical Study. Phase 1

Science.gov (United States)

1998-01-01

The aviation community is faced with reducing the fatal aircraft accident rate by 80 percent within 10 years. This must be achieved even with ever increasing, traffic and a changing National Airspace System. This is not just an altruistic goal, but a real necessity, if our growing level of commerce is to continue. Honeywell Technology Center's topical study, "Weather Avoidance Using Route Optimization as a Decision Aid", addresses these pressing needs. The goal of this program is to use route optimization and user interface technologies to develop a prototype decision aid for dispatchers and pilots. This decision aid will suggest possible diversions through single or multiple weather hazards and present weather information with a human-centered design. At the conclusion of the program, we will have a laptop prototype decision aid that will be used to demonstrate concepts to industry for integration into commercialized products for dispatchers and/or pilots. With weather a factor in 30% of aircraft accidents, our program will prevent accidents by strategically avoiding weather hazards in flight. By supplying more relevant weather information in a human-centered format along with the tools to generate flight plans around weather, aircraft exposure to weather hazards can be reduced. Our program directly addresses the NASA's five year investment areas of Strategic Weather Information and Weather Operations (simulation/hazard characterization and crew/dispatch/ATChazard monitoring, display, and decision support) (NASA Aeronautics Safety Investment Strategy: Weather Investment Recommendations, April 15, 1997). This program is comprised of two phases, Phase I concluded December 31, 1998. This first phase defined weather data requirements, lateral routing algorithms, an conceptual displays for a user-centered design. Phase II runs from January 1999 through September 1999. The second phase integrates vertical routing into the lateral optimizer and combines the user

Decision support systems in nuclear emergencies: harmonizing domestic and reference tools

International Nuclear Information System (INIS)

Vamanu, D.; Mateescu, Gh.; Berinde, A.; Slavnicu, D.; Acasandrei, V.; Slavnicu, E.

2001-01-01

The paper addresses the issue of securing the compatibility and inter-operability of computer packages designed to perform as decision support tools in the management of radiological emergencies, over the transition times towards the implementation and uniform acceptance and uniform acceptance of internationally-shared reference tools such as the European Union's RODOS (Real Time On-Line Decision Support System for Off-Site Nuclear Emergencies in Europe). One submits that a harmonization between the currently operational, domestic, and the reference tool can be contemplated, based on extensive code comparison and benchmarking. A case in point is presented, paralleling selected RODOS applications on simulated abnormal nuclear events, and the concurrent application of a resident software package, NOTEPAD, developed to emulate RODOS-wise function at IFIH-HH Bucharest. The reproducible similarity may make domestic decision support system (DSS) facilities useful as both practical tools and factors promoting the emergency preparedness awareness, during the interim time laps till the full development and deployment of RODOS as a reference DSS in Europe. (authors)

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems

Science.gov (United States)

Kerstman, Eric; Minard, Charles; Saile, Lynn; deCarvalho, Mary Freire; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David

2009-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.

External costs in the global energy optimization models. A tool in favour of sustain ability

International Nuclear Information System (INIS)

Cabal Cuesta, H.

2007-01-01

The aim of this work is the analysis of the effects of the GHG external costs internalization in the energy systems. This may provide a useful tool to support decision makers to help reaching the energy systems sustain ability. External costs internalization has been carried out using two methods. First, CO 2 externalities of different power generation technologies have been internalized to evaluate their effects on the economic competitiveness of these present and future technologies. The other method consisted of analysing and optimizing the global energy system, from an economic and environmental point of view, using the global energy optimization model generator, TIMES, with a time horizon of 50 years. Finally, some scenarios regarding environmental and economic strategic measures have been analysed. (Author)

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

Science.gov (United States)

Patrick, Nicholas J. M.; Sheridan, Thomas B.

1996-01-01

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance vary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are: (1) determining what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major u.s. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort-topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with

Optimizing Negotiation Conflict in the Cloud Service Negotiation Framework Using Probabilistic Decision Making Model.

Science.gov (United States)

Rajavel, Rajkumar; Thangarathinam, Mala

2015-01-01

Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework.

Informing vaccine decision-making: A strategic multi-attribute ranking tool for vaccines-SMART Vaccines 2.0.

Science.gov (United States)

Knobler, Stacey; Bok, Karin; Gellin, Bruce

2017-01-20

SMART Vaccines 2.0 software is being developed to support decision-making among multiple stakeholders in the process of prioritizing investments to optimize the outcomes of vaccine development and deployment. Vaccines and associated vaccination programs are one of the most successful and effective public health interventions to prevent communicable diseases and vaccine researchers are continually working towards expanding targets for communicable and non-communicable diseases through preventive and therapeutic modes. A growing body of evidence on emerging vaccine technologies, trends in disease burden, costs associated with vaccine development and deployment, and benefits derived from disease prevention through vaccination and a range of other factors can inform decision-making and investment in new and improved vaccines and targeted utilization of already existing vaccines. Recognizing that an array of inputs influences these decisions, the strategic multi-attribute ranking method for vaccines (SMART Vaccines 2.0) is in development as a web-based tool-modified from a U.S. Institute of Medicine Committee effort (IOM, 2015)-to highlight data needs and create transparency to facilitate dialogue and information-sharing among decision-makers and to optimize the investment of resources leading to improved health outcomes. Current development efforts of the SMART Vaccines 2.0 framework seek to generate a weighted recommendation on vaccine development or vaccination priorities based on population, disease, economic, and vaccine-specific data in combination with individual preference and weights of user-selected attributes incorporating valuations of health, economics, demographics, public concern, scientific and business, programmatic, and political considerations. Further development of the design and utility of the tool is being carried out by the National Vaccine Program Office of the Department of Health and Human Services and the Fogarty International Center of the

NonLinear Parallel OPtimization Tool, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — The technological advancement proposed is a novel large-scale Noninear Parallel OPtimization Tool (NLPAROPT). This software package will eliminate the computational...

Optimization of decision rules based on dynamic programming approach

KAUST Repository

Zielosko, Beata

2014-01-14

This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.

Collaboration and decision making tools for mobile groups

International Nuclear Information System (INIS)

Abrahamyan, S.; Balyan, S.; Degtyarev, A.; Ter-Minasyan, H.

2017-01-01

Nowadays the use of distributed collaboration tools is widespread in many areas of people activity. But lack of mobility and certain equipment dependence create difficulties and decelerate development and integration of such technologies. Also, mobile technologies allow individuals to interact with each other without need of traditional office spaces and regardless of location. Hence, realization of special infrastructures on mobile platforms with the help of ad hoc wireless local networks could eliminate hardware attachment and be also useful in terms of scientific approach. Solutions from basic internet messengers to complex software for online collaboration equipment in large-scale workgroups are implementations of tools based on mobile infrastructures. Despite growth of mobile infrastructures, applied distributed solutions in group decision-making and e-collaboration are not common. In this article we propose software complex for real-time collaboration and decision-making based on mobile devices, describe its architecture and evaluate performance.

Decision support tools : midterm review report Knowledge for Climate Theme 8

NARCIS (Netherlands)

Ierland, van E.C.

2012-01-01

The KfC program Decision Support Tools aims at improving tools for design and evaluation of adaptation strategies with a special focus on spatial planning and cross cutting issues. The program focuses on three core elements 1. tools for formulation of the adaptation task, based on climate scenarios

A modeling tool to support decision making in future hydropower development in Chile

Science.gov (United States)

Vicuna, S.; Hermansen, C.; Cerda, J. P.; Olivares, M. A.; Gomez, T. I.; Toha, E.; Poblete, D.; Mao, L.; Falvey, M. J.; Pliscoff, P.; Melo, O.; Lacy, S.; Peredo, M.; Marquet, P. A.; Maturana, J.; Gironas, J. A.

2017-12-01

Modeling tools support planning by providing transparent means to assess the outcome of natural resources management alternatives within technical frameworks in the presence of conflicting objectives. Such tools, when employed to model different scenarios, complement discussion in a policy-making context. Examples of practical use of this type of tool exist, such as the Canadian public forest management, but are not common, especially in the context of developing countries. We present a tool to support the selection from a portfolio of potential future hydropower projects in Chile. This tool, developed by a large team of researchers under the guidance of the Chilean Energy Ministry, is especially relevant in the context of evident regionalism, skepticism and change in societal values in a country that has achieved a sustained growth alongside increased demands from society. The tool operates at a scale of a river reach, between 1-5 km long, on a domain that can be defined according to the scale needs of the related discussion, and its application can vary from river basins to regions or other spatial configurations that may be of interest. The tool addresses both available hydropower potential and the existence (inferred or observed) of other ecological, social, cultural and productive characteristics of the territory which are valuable to society, and provides a means to evaluate their interaction. The occurrence of each of these other valuable characteristics in the territory is measured by generating a presence-density score for each. Considering the level of constraint each characteristic imposes on hydropower development, they are weighted against each other and an aggregate score is computed. With this information, optimal trade-offs are computed between additional hydropower capacity and valuable local characteristics over the entire domain, using the classical knapsack 0-1 optimization algorithm. Various scenarios of different weightings and hydropower

Optimization-based decision support to assist in logistics planning for hospital evacuations.

Science.gov (United States)

Glick, Roger; Bish, Douglas R; Agca, Esra

2013-01-01

The evacuation of the hospital is a very complex process and evacuation planning is an important part of a hospital's emergency management plan. There are numerous factors that affect the evacuation plan including the nature of threat, availability of resources and staff the characteristics of the evacuee population, and risk to patients and staff. The safety and health of patients is of fundamental importance, but safely moving patients to alternative care facilities while under threat is a very challenging task. This article describes the logistical issues and complexities involved in planning and execution of hospital evacuations. Furthermore, this article provides examples of how optimization-based decision support tools can help evacuation planners to better plan for complex evacuations by providing real-world solutions to various evacuation scenarios.

Research on the decision-making model of land-use spatial optimization

Science.gov (United States)

He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

2009-10-01

Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis

International Nuclear Information System (INIS)

Jesneck, Jonathan L.; Nolte, Loren W.; Baker, Jay A.; Floyd, Carey E.; Lo, Joseph Y.

2006-01-01

As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p<0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets

Making the Optimal Decision in Selecting Protective Clothing

International Nuclear Information System (INIS)

Price, J. Mark

2008-01-01

Protective Clothing plays a major role in the decommissioning and operation of nuclear facilities. Literally thousands of dress-outs occur over the life of a decommissioning project and during outages at operational plants. In order to make the optimal decision on which type of protective clothing is best suited for the decommissioning or maintenance and repair work on radioactive systems, a number of interrelating factors must be considered. This article discusses these factors as well as surveys of plants regarding their level of usage of single use protective clothing and should help individuals making decisions about protective clothing as it applies to their application. Individuals considering using SUPC should not jump to conclusions. The survey conducted clearly indicates that plants have different drivers. An evaluation should be performed to understand the facility's true drivers for selecting clothing. It is recommended that an interdisciplinary team be formed including representatives from budgets and cost, safety, radwaste, health physics, and key user groups to perform the analysis. The right questions need to be asked and answered by the company providing the clothing to formulate a proper perspective and conclusion. The conclusions and recommendations need to be shared with senior management so that the drivers, expected results, and associated costs are understood and endorsed. In the end, the individual making the recommendation should ask himself/herself: 'Is my decision emotional, or logical and economical?' 'Have I reached the optimal decision for my plant?'

Tool Support for Software Lookup Table Optimization

Directory of Open Access Journals (Sweden)

Chris Wilcox

2011-01-01

Full Text Available A number of scientific applications are performance-limited by expressions that repeatedly call costly elementary functions. Lookup table (LUT optimization accelerates the evaluation of such functions by reusing previously computed results. LUT methods can speed up applications that tolerate an approximation of function results, thereby achieving a high level of fuzzy reuse. One problem with LUT optimization is the difficulty of controlling the tradeoff between performance and accuracy. The current practice of manual LUT optimization adds programming effort by requiring extensive experimentation to make this tradeoff, and such hand tuning can obfuscate algorithms. In this paper we describe a methodology and tool implementation to improve the application of software LUT optimization. Our Mesa tool implements source-to-source transformations for C or C++ code to automate the tedious and error-prone aspects of LUT generation such as domain profiling, error analysis, and code generation. We evaluate Mesa with five scientific applications. Our results show a performance improvement of 3.0× and 6.9× for two molecular biology algorithms, 1.4× for a molecular dynamics program, 2.1× to 2.8× for a neural network application, and 4.6× for a hydrology calculation. We find that Mesa enables LUT optimization with more control over accuracy and less effort than manual approaches.

Optimizing Negotiation Conflict in the Cloud Service Negotiation Framework Using Probabilistic Decision Making Model

Directory of Open Access Journals (Sweden)

Rajkumar Rajavel

2015-01-01

Full Text Available Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework.

Mathematical optimization of incore nuclear fuel management decisions: Status and trends

International Nuclear Information System (INIS)

Turinsky, P.J.

1999-01-01

Nuclear fuel management involves making decisions about the number of fresh assemblies to purchase and their Attributes (e.g. enrichment and burnable poison loading), burnt fuel to reinsert, location of the assemblies in the core (i.e. loading pattern (LP)), and insertion of control rods as a function of cycle exposure (i.e. control rod pattern (CRP)). The out-of-core and incore nuclear fuel management problems denote an artificial separation of decisions to simplify the decisionmaking. The out-of-core problem involves multicycle analysis so that levelized fuel cycle cost can be evaluated; whereas, the incore problem normally involves single cycle analysis. Decision variables for the incore problem normally include all of the above noted decisions with the exception of the number of fresh assemblies, which is restricted by discharge burnup limits and therefore involves multicycle considerations. This paper reports on the progress that is being made in addressing the incore nuclear fuel management problem utilizing formal mathematical optimization methods. Advances in utilizing the Simulating Annealing, Genetic Algorithm and Tabu Search methods, with applications to pressurized and boiling water reactor incore optimization problem, will be reviewed. Recent work on the addition of multiobjective optimization capability to aide the decision maker, and utilization of heuristic rules and incorporation of parallel algorithms to increase computational efficiency, will be discussed. (orig.) [de

Intra-annual wave resource characterization for energy exploitation: A new decision-aid tool

International Nuclear Information System (INIS)

Carballo, R.; Sánchez, M.; Ramos, V.; Fraguela, J.A.; Iglesias, G.

2015-01-01

Highlights: • A decision-aid tool is developed for computing the monthly performance of WECs. • It allows the generation of high-resolution monthly characterization matrices. • The decision-aid tool is implemented to the Death Coast (N Spain). • The monthly matrices can be obtained at any coastal location within the Death Coast. • The tool is applied to a coastal location of a proposed wave farm. - Abstract: The wave energy resource is usually characterized by a significant variability throughout the year. In estimating the power performance of a Wave Energy Converter (WEC) it is fundamental to take into account this variability; indeed, an estimate based on mean annual values may well result in a wrong decision making. In this work, a novel decision-aid tool, iWEDGE (intra-annual Wave Energy Diagram GEnerator) is developed and implemented to a coastal region of interest, the Death Coast (Spain), one of the regions in Europe with the largest wave resource. Following a comprehensive procedure, and based on deep water wave data and high-resolution numerical modelling, this tool provides the monthly high-resolution characterization matrices (or energy diagrams) for any location of interest. In other words, the information required for the accurate computation of the intra-annual performance of any WEC at any location within the region covered is made available. Finally, an application of iWEDGE to the site of a proposed wave farm is presented. The results obtained highlight the importance of the decision-aid tool herein provided for wave energy exploitation

A cognitive decision agent architecture for optimal energy management of microgrids

International Nuclear Information System (INIS)

Velik, Rosemarie; Nicolay, Pascal

2014-01-01

Highlights: • We propose an optimization approach for energy management in microgrids. • The optimizer emulates processes involved in human decision making. • Optimization objectives are energy self-consumption and financial gain maximization. • We gain improved optimization results in significantly reduced computation time. - Abstract: Via the integration of renewable energy and storage technologies, buildings have started to change from passive (electricity) consumers to active prosumer microgrids. Along with this development come a shift from centralized to distributed production and consumption models as well as discussions about the introduction of variable demand–supply-driven grid electricity prices. Together with upcoming ICT and automation technologies, these developments open space to a wide range of novel energy management and energy trading possibilities to optimally use available energy resources. However, what is considered as an optimal energy management and trading strategy heavily depends on the individual objectives and needs of a microgrid operator. Accordingly, elaborating the most suitable strategy for each particular system configuration and operator need can become quite a complex and time-consuming task, which can massively benefit from computational support. In this article, we introduce a bio-inspired cognitive decision agent architecture for optimized, goal-specific energy management in (interconnected) microgrids, which are additionally connected to the main electricity grid. For evaluating the performance of the architecture, a number of test cases are specified targeting objectives like local photovoltaic energy consumption maximization and financial gain maximization. Obtained outcomes are compared against a modified simulating annealing optimization approach in terms of objective achievement and computational effort. Results demonstrate that the cognitive decision agent architecture yields improved optimization results in

Value based building renovation - A tool for decision-making and evaluation

DEFF Research Database (Denmark)

Jensen, Per Anker; Maslesa, Esmir

2015-01-01

Research on the barriers for building renovation in Denmark has revealed that an important obstacle is a lack of simple and holistic tools that can assist stakeholders in prioritisation and decision-making during the early stages of building renovation projects. The purpose of this article...... is to present a tool - RENO-EVALUE, which can be used as decision support for sustainable renovation projects, and for evaluation, during and after building renovations. The tool is a result from the European Eracobuild project ACES - "A concept for promotion of sustainable retrofitting and renovation in early...... stages". This article presents the main result of a work package concerning benefits of renovation. RENO-EVALUE has been developed from four case studies on renovation projects in Denmark, tested and validated on the cases and in a Delphi study. The tool is value based by focusing on the different...

Understanding the stakeholders' intention to use economic decision-support tools: A cross-sectional study with the tobacco return on investment tool.

Science.gov (United States)

Cheung, Kei Long; Evers, Silvia M A A; Hiligsmann, Mickaël; Vokó, Zoltán; Pokhrel, Subhash; Jones, Teresa; Muñoz, Celia; Wolfenstetter, Silke B; Józwiak-Hagymásy, Judit; de Vries, Hein

2016-01-01

Despite an increased number of economic evaluations of tobacco control interventions, the uptake by stakeholders continues to be limited. Understanding the underlying mechanism in adopting such economic decision-support tools by stakeholders is therefore important. By applying the I-Change Model, this study aims to identify which factors determine potential uptake of an economic decision-support tool, i.e., the Return on Investment tool. Stakeholders (decision-makers, purchasers of services/pharma products, professionals/service providers, evidence generators and advocates of health promotion) were interviewed in five countries, using an I-Change based questionnaire. MANOVA's were conducted to assess differences between intenders and non-intenders regarding beliefs. A multiple regression analysis was conducted to identify the main explanatory variables of intention to use an economic decision-support tool. Ninety-three stakeholders participated. Significant differences in beliefs were found between non-intenders and intenders: risk perception, attitude, social support, and self-efficacy towards using the tool. Regression showed that demographics, pre-motivational, and motivational factors explained 69% of the variation in intention. This study is the first to provide a theoretical framework to understand differences in beliefs between stakeholders who do or do not intend to use economic decision-support tools, and empirically corroborating the framework. This contributes to our understanding of the facilitators and barriers to the uptake of these studies. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Optimally Locating MARFORRES Units

OpenAIRE

Salmeron, Javier; Dell, Rob

2015-01-01

Javier Salmeron and Rob Dell The U.S. Marine Forces Reserve (USMCR, MARFORRES) is conducting realignment studies where discretionary changes may benefit from formal mathematical analysis. This study has developed an optimization tool to guide and/or support Commander, MARFORRES (CMFR) decisions. A prototype of the optimization tool has been tested with data from the units and Reserve Training Centers (RTCs) in the San Francisco, CA and Sacramento, CA areas. Prepared for: MARFORRES, POC:...

Application of Bayesian statistical decision theory to the optimization of generating set maintenance

International Nuclear Information System (INIS)

Procaccia, H.; Cordier, R.; Muller, S.

1994-07-01

Statistical decision theory could be a alternative for the optimization of preventive maintenance periodicity. In effect, this theory concerns the situation in which a decision maker has to make a choice between a set of reasonable decisions, and where the loss associated to a given decision depends on a probabilistic risk, called state of nature. In the case of maintenance optimization, the decisions to be analyzed are different periodicities proposed by the experts, given the observed feedback experience, the states of nature are the associated failure probabilities, and the losses are the expectations of the induced cost of maintenance and of consequences of the failures. As failure probabilities concern rare events, at the ultimate state of RCM analysis (failure of sub-component), and as expected foreseeable behaviour of equipment has to be evaluated by experts, Bayesian approach is successfully used to compute states of nature. In Bayesian decision theory, a prior distribution for failure probabilities is modeled from expert knowledge, and is combined with few stochastic information provided by feedback experience, giving a posterior distribution of failure probabilities. The optimized decision is the decision that minimizes the expected loss over the posterior distribution. This methodology has been applied to inspection and maintenance optimization of cylinders of diesel generator engines of 900 MW nuclear plants. In these plants, auxiliary electric power is supplied by 2 redundant diesel generators which are tested every 2 weeks during about 1 hour. Until now, during yearly refueling of each plant, one endoscopic inspection of diesel cylinders is performed, and every 5 operating years, all cylinders are replaced. RCM has shown that cylinder failures could be critical. So Bayesian decision theory has been applied, taking into account expert opinions, and possibility of aging when maintenance periodicity is extended. (authors). 8 refs., 5 figs., 1 tab

A decision support tool for appropriate glucose-lowering therapy in patients with type 2 diabetes.

Science.gov (United States)

Ampudia-Blasco, F Javier; Benhamou, Pierre Yves; Charpentier, Guillaume; Consoli, Agostino; Diamant, Michaela; Gallwitz, Baptist; Khunti, Kamlesh; Mathieu, Chantal; Ridderstråle, Martin; Seufert, Jochen; Tack, Cees; Vilsbøll, Tina; Phan, Tra-Mi; Stoevelaar, Herman

2015-03-01

Optimal glucose-lowering therapy in type 2 diabetes mellitus requires a patient-specific approach. Although a good framework, current guidelines are insufficiently detailed to address the different phenotypes and individual needs of patients seen in daily practice. We developed a patient-specific decision support tool based on a systematic analysis of expert opinion. Based on the American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) 2012 position statement, a panel of 12 European experts rated the appropriateness (RAND/UCLA Appropriateness Method) of treatment strategies for 930 clinical scenarios, which were permutations of clinical variables considered relevant to treatment choice. These included current treatment, hemoglobin A1c difference from individualized target, risk of hypoglycemia, body mass index, life expectancy, and comorbidities. Treatment options included addition of a second or third agent, drug switches, and replacement by monotherapies if the patient was metformin-intolerant. Treatment costs were not considered. Appropriateness (appropriate, inappropriate, uncertain) was based on the median score and expert agreement. The panel recommendations were embedded in an online decision support tool (DiaScope(®); Novo Nordisk Health Care AG, Zürich, Switzerland). Treatment appropriateness was associated with (combinations of) the patient variables mentioned above. As second-line agents, dipeptidyl peptidase-4 inhibitors were considered appropriate in all scenarios, followed by glucagon-like peptide-1 receptor agonists (50%), insulins (33%), and sulfonylureas (25%), but not pioglitazone (0%). Ratings of third-line combinations followed a similar pattern. Disagreement was highest for regimens including pioglitazone, sulfonylureas, or insulins and was partly due to differences in panelists' opinions and in drug availability and reimbursement across European countries (although costs were disregarded in the rating process

Optimization-based decision support systems for planning problems in processing industries

NARCIS (Netherlands)

Claassen, G.D.H.

2014-01-01

Summary

Optimization-based decision support systems for planning problems in processing industries

Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in

Decision making based on data analysis and optimization algorithm applied for cogeneration systems integration into a grid

Science.gov (United States)

Asmar, Joseph Al; Lahoud, Chawki; Brouche, Marwan

2018-05-01

Cogeneration and trigeneration systems can contribute to the reduction of primary energy consumption and greenhouse gas emissions in residential and tertiary sectors, by reducing fossil fuels demand and grid losses with respect to conventional systems. The cogeneration systems are characterized by a very high energy efficiency (80 to 90%) as well as a less polluting aspect compared to the conventional energy production. The integration of these systems into the energy network must simultaneously take into account their economic and environmental challenges. In this paper, a decision-making strategy will be introduced and is divided into two parts. The first one is a strategy based on a multi-objective optimization tool with data analysis and the second part is based on an optimization algorithm. The power dispatching of the Lebanese electricity grid is then simulated and considered as a case study in order to prove the compatibility of the cogeneration power calculated by our decision-making technique. In addition, the thermal energy produced by the cogeneration systems which capacity is selected by our technique shows compatibility with the thermal demand for district heating.

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

Science.gov (United States)

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratiodecisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

Requirements for advanced decision support tools in future distribution network planning

NARCIS (Netherlands)

Grond, M.O.W.; Morren, J.; Slootweg, J.G.

2013-01-01

This paper describes the need and requirements for advanced decision support tools in future network planning from a distribution network operator perspective. The existing tools will no longer be satisfactory for future application due to present developments in the electricity sector that increase

Extension of an Object-Oriented Optimization Tool: User's Reference Manual

Science.gov (United States)

Pak, Chan-Gi; Truong, Samson S.

2015-01-01

The National Aeronautics and Space Administration Armstrong Flight Research Center has developed a cost-effective and flexible object-oriented optimization (O (sup 3)) tool that leverages existing tools and practices and allows easy integration and adoption of new state-of-the-art software. This object-oriented framework can integrate the analysis codes for multiple disciplines, as opposed to relying on one code to perform analysis for all disciplines. Optimization can thus take place within each discipline module, or in a loop between the O (sup 3) tool and the discipline modules, or both. Six different sample mathematical problems are presented to demonstrate the performance of the O (sup 3) tool. Instructions for preparing input data for the O (sup 3) tool are detailed in this user's manual.

Evolutionary Artificial Neural Network Weight Tuning to Optimize Decision Making for an Abstract Game

Science.gov (United States)

2010-03-01

EVOLUTIONARY ARTIFICIAL NEURAL NETWORK WEIGHT TUNING TO OPTIMIZE DECISION MAKING FOR AN ABSTRACT...AFIT/GCS/ENG/10-06 EVOLUTIONARY ARTIFICIAL NEURAL NETWORK WEIGHT TUNING TO OPTIMIZE DECISION MAKING FOR AN ABSTRACT GAME THESIS Presented...35 14: Diagram of pLoGANN’s Artificial Neural Network and

Optimal decision making on the basis of evidence represented in spike trains.

Science.gov (United States)

Zhang, Jiaxiang; Bogacz, Rafal

2010-05-01

Experimental data indicate that perceptual decision making involves integration of sensory evidence in certain cortical areas. Theoretical studies have proposed that the computation in neural decision circuits approximates statistically optimal decision procedures (e.g., sequential probability ratio test) that maximize the reward rate in sequential choice tasks. However, these previous studies assumed that the sensory evidence was represented by continuous values from gaussian distributions with the same variance across alternatives. In this article, we make a more realistic assumption that sensory evidence is represented in spike trains described by the Poisson processes, which naturally satisfy the mean-variance relationship observed in sensory neurons. We show that for such a representation, the neural circuits involving cortical integrators and basal ganglia can approximate the optimal decision procedures for two and multiple alternative choice tasks.

Determination of optimal pollution levels through multiple-criteria decision making: an application to the Spanish electricity sector

International Nuclear Information System (INIS)

Linares, P.

1999-01-01

An efficient pollution management requires the harmonisation of often conflicting economic and environmental aspects. A compromise has to be found, in which social welfare is maximised. The determination of this social optimum has been attempted with different tools, of which the most correct according to neo-classical economics may be the one based on the economic valuation of the externalities of pollution. However, this approach is still controversial, and few decision makers trust the results obtained enough to apply them. But a very powerful alternative exists, which avoids the problem of monetizing physical impacts. Multiple-criteria decision making provides methodologies for dealing with impacts in different units, and for incorporating the preferences of decision makers or society as a whole, thus allowing for the determination of social optima under heterogeneous criteria, which is usually the case of pollution management decisions. In this paper, a compromise programming model is presented for the determination of the optimal pollution levels for the electricity industry in Spain for carbon dioxide, sulphur dioxide, nitrous oxides, and radioactive waste. The preferences of several sectors of society are incorporated explicitly into the model, so that the solution obtained represents the optimal pollution level from a social point of view. Results show that cost minimisation is still the main objective for society, but the simultaneous consideration of the rest of the criteria achieves large pollution reductions at a low cost increment. (Author)

Nonlinear Shaping Architecture Designed with Using Evolutionary Structural Optimization Tools

Science.gov (United States)

Januszkiewicz, Krystyna; Banachowicz, Marta

2017-10-01

The paper explores the possibilities of using Structural Optimization Tools (ESO) digital tools in an integrated structural and architectural design in response to the current needs geared towards sustainability, combining ecological and economic efficiency. The first part of the paper defines the Evolutionary Structural Optimization tools, which were developed specifically for engineering purposes using finite element analysis as a framework. The development of ESO has led to several incarnations, which are all briefly discussed (Additive ESO, Bi-directional ESO, Extended ESO). The second part presents result of using these tools in structural and architectural design. Actual building projects which involve optimization as a part of the original design process will be presented (Crematorium in Kakamigahara Gifu, Japan, 2006 SANAA“s Learning Centre, EPFL in Lausanne, Switzerland 2008 among others). The conclusion emphasizes that the structural engineering and architectural design mean directing attention to the solutions which are used by Nature, designing works optimally shaped and forming their own environments. Architectural forms never constitute the optimum shape derived through a form-finding process driven only by structural optimization, but rather embody and integrate a multitude of parameters. It might be assumed that there is a similarity between these processes in nature and the presented design methods. Contemporary digital methods make the simulation of such processes possible, and thus enable us to refer back to the empirical methods of previous generations.

Antagonistic and Bargaining Games in Optimal Marketing Decisions

Science.gov (United States)

Lipovetsky, S.

2007-01-01

Game theory approaches to find optimal marketing decisions are considered. Antagonistic games with and without complete information, and non-antagonistic games techniques are applied to paired comparison, ranking, or rating data for a firm and its competitors in the market. Mix strategy, equilibrium in bi-matrix games, bargaining models with…

The role of depression pharmacogenetic decision support tools in shared decision making.

Science.gov (United States)

Arandjelovic, Katarina; Eyre, Harris A; Lenze, Eric; Singh, Ajeet B; Berk, Michael; Bousman, Chad

2017-10-29

Patients discontinue antidepressant medications due to lack of knowledge, unrealistic expectations, and/or unacceptable side effects. Shared decision making (SDM) invites patients to play an active role in their treatment and may indirectly improve outcomes through enhanced engagement in care, adherence to treatment, and positive expectancy of medication outcomes. We believe decisional aids, such as pharmacogenetic decision support tools (PDSTs), facilitate SDM in the clinical setting. PDSTs may likewise predict drug tolerance and efficacy, and therefore adherence and effectiveness on an individual-patient level. There are several important ethical considerations to be navigated when integrating PDSTs into clinical practice. The field requires greater empirical research to demonstrate clinical utility, and the mechanisms thereof, as well as exploration of the ethical use of these technologies.

Identification of Optimal Policies in Markov Decision Processes

Czech Academy of Sciences Publication Activity Database

Sladký, Karel

46 2010, č. 3 (2010), s. 558-570 ISSN 0023-5954. [International Conference on Mathematical Methods in Economy and Industry. České Budějovice, 15.06.2009-18.06.2009] R&D Projects: GA ČR(CZ) GA402/08/0107; GA ČR GA402/07/1113 Institutional research plan: CEZ:AV0Z10750506 Keywords : finite state Markov decision processes * discounted and average costs * elimination of suboptimal policies Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.461, year: 2010 http://library.utia.cas.cz/separaty/2010/E/sladky-identification of optimal policies in markov decision processes.pdf

Where should I send it? Optimizing the submission decision process.

Directory of Open Access Journals (Sweden)

Santiago Salinas

Full Text Available How do scientists decide where to submit manuscripts? Many factors influence this decision, including prestige, acceptance probability, turnaround time, target audience, fit, and impact factor. Here, we present a framework for evaluating where to submit a manuscript based on the theory of Markov decision processes. We derive two models, one in which an author is trying to optimally maximize citations and another in which that goal is balanced by either minimizing the number of resubmissions or the total time in review. We parameterize the models with data on acceptance probability, submission-to-decision times, and impact factors for 61 ecology journals. We find that submission sequences beginning with Ecology Letters, Ecological Monographs, or PLOS ONE could be optimal depending on the importance given to time to acceptance or number of resubmissions. This analysis provides some guidance on where to submit a manuscript given the individual-specific values assigned to these disparate objectives.

Comparative Multi-Criteria Assessment of Climate Policies and Sustainable Development Strategies in Cameroon: Towards a GIS Decision-Support Tool for the Design of an Optimal REDD+ Strategy

Directory of Open Access Journals (Sweden)

Anderson Gwanyebit Kehbila

2014-09-01

Full Text Available Cameroon is committed to reducing emissions from deforestation and forest degradation plus conservation, sustainable management of forests and enhancement of carbon stocks (REDD+. To achieve this goal, the government has introduced a series of policy reforms and formulated a number of key strategic planning documents to advance the REDD+ readiness process in Cameroon. This paper assesses the extent to which major cross-sectoral policies support or impede the development and implementation of an optimal REDD+ strategy in Cameroon from a comparative multi-criteria perspective. Study results reveal that a majority of the policy instruments reviewed appeared to be less prescriptive in terms of any tangible REDD+ strategy, as they do not have provisions for tangible measures to reduce deforestation and forest degradation. Given the lack of adequate flexibility, prompt review and responsiveness of these cross-sectoral policies to adapt themselves to new realities and respond to a changing environment, this paper introduces a GIS-REDD+ decision support system (GIS-REDD+DSS that is necessary to support the adaptive element of an adaptive REDD+ strategy in Cameroon. The GIS-REDD+DSS, an electronic REDD+agri intermediary hub, serves the following purpose: (1 host a database of locally-relevant climate information, improved input technologies, best practices as well as land use and forest cover geo-spatial maps; (2 host a virtual economic tool that performs economic valuations (costs and benefits and financial analysis of REDD+agri projects to aid investment decision-making; and (3 host an electronic marketplace to mediate any-to-any transactions among REDD+agri project developers, service providers, input suppliers, private and institutional investors and buyers (wholesalers and retailers, thereby creating value in two ways: aggregation and matching. This decision support tool, we argue, is a fundamental prerequisite for “policy and REDD+ safeguard

Q-Learning Multi-Objective Sequential Optimal Sensor Parameter Weights

Directory of Open Access Journals (Sweden)

Raquel Cohen

2016-04-01

Full Text Available The goal of our solution is to deliver trustworthy decision making analysis tools which evaluate situations and potential impacts of such decisions through acquired information and add efficiency for continuing mission operations and analyst information.We discuss the use of cooperation in modeling and simulation and show quantitative results for design choices to resource allocation. The key contribution of our paper is to combine remote sensing decision making with Nash Equilibrium for sensor parameter weighting optimization. By calculating all Nash Equilibrium possibilities per period, optimization of sensor allocation is achieved for overall higher system efficiency. Our tool provides insight into what are the most important or optimal weights for sensor parameters and can be used to efficiently tune those weights.

Combining multi-criteria decision analysis and mini-health technology assessment: A funding decision-support tool for medical devices in a university hospital setting.

Science.gov (United States)

Martelli, Nicolas; Hansen, Paul; van den Brink, Hélène; Boudard, Aurélie; Cordonnier, Anne-Laure; Devaux, Capucine; Pineau, Judith; Prognon, Patrice; Borget, Isabelle

2016-02-01

At the hospital level, decisions about purchasing new and oftentimes expensive medical devices must take into account multiple criteria simultaneously. Multi-criteria decision analysis (MCDA) is increasingly used for health technology assessment (HTA). One of the most successful hospital-based HTA approaches is mini-HTA, of which a notable example is the Matrix4value model. To develop a funding decision-support tool combining MCDA and mini-HTA, based on Matrix4value, suitable for medical devices for individual patient use in French university hospitals - known as the IDA tool, short for 'innovative device assessment'. Criteria for assessing medical devices were identified from a literature review and a survey of 18 French university hospitals. Weights for the criteria, representing their relative importance, were derived from a survey of 25 members of a medical devices committee using an elicitation technique involving pairwise comparisons. As a test of its usefulness, the IDA tool was applied to two new drug-eluting beads (DEBs) for transcatheter arterial chemoembolization. The IDA tool comprises five criteria and weights for each of two over-arching categories: risk and value. The tool revealed that the two new DEBs conferred no additional value relative to DEBs currently available. Feedback from participating decision-makers about the IDA tool was very positive. The tool could help to promote a more structured and transparent approach to HTA decision-making in French university hospitals. Copyright © 2015 Elsevier Inc. All rights reserved.

Dynamic programming approach to optimization of approximate decision rules

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number

Artificial intelligence tools decision support systems in condition monitoring and diagnosis

CERN Document Server

Galar Pascual, Diego

2015-01-01

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

Optimization Specifications for CUDA Code Restructuring Tool

KAUST Repository

Khan, Ayaz

2017-03-13

In this work we have developed a restructuring software tool (RT-CUDA) following the proposed optimization specifications to bridge the gap between high-level languages and the machine dependent CUDA environment. RT-CUDA takes a C program and convert it into an optimized CUDA kernel with user directives in a configuration file for guiding the compiler. RTCUDA also allows transparent invocation of the most optimized external math libraries like cuSparse and cuBLAS enabling efficient design of linear algebra solvers. We expect RT-CUDA to be needed by many KSA industries dealing with science and engineering simulation on massively parallel computers like NVIDIA GPUs.

Optimal contracts decision of industrial customers

International Nuclear Information System (INIS)

Tsay, M.-T.; Lin, W.-M.; Lee, J.-L.

2001-01-01

This paper develops a software package to calculate the optimal contract capacities for industrial customers. Based on the time-of-use (TOU) rates employed by the Taiwan Power Company, the objective function is formulated, to minimize the electricity bill of industrial customers during the whole year period. Evolutionary programming (EP) was adopted to solve this problem. Users can get the optimal contract capacities for the peak load, semi-peak load, and off-peak load, respectively. Practical load consumption data were used to prove the validity of this program. Results show that the software developed in this paper can be used as a useful tool for industrial customers in selecting contract capacities to curtail the electricity bill. (author)

Stakeholder views of management and decision support tools to integrate climate change into Great Lakes Lake Whitefish management

Science.gov (United States)

Lynch, Abigail J.; Taylor, William W.; McCright, Aaron M.

2016-01-01

Decision support tools can aid decision making by systematically incorporating information, accounting for uncertainties, and facilitating evaluation between alternatives. Without user buy-in, however, decision support tools can fail to influence decision-making processes. We surveyed fishery researchers, managers, and fishers affiliated with the Lake Whitefish Coregonus clupeaformis fishery in the 1836 Treaty Waters of Lakes Huron, Michigan, and Superior to assess opinions of current and future management needs to identify barriers to, and opportunities for, developing a decision support tool based on Lake Whitefish recruitment projections with climate change. Approximately 64% of 39 respondents were satisfied with current management, and nearly 85% agreed that science was well integrated into management programs. Though decision support tools can facilitate science integration into management, respondents suggest that they face significant implementation barriers, including lack of political will to change management and perceived uncertainty in decision support outputs. Recommendations from this survey can inform development of decision support tools for fishery management in the Great Lakes and other regions.

Optimization-based decision support systems for planning problems in processing industries

OpenAIRE

Claassen, G.D.H.

2014-01-01

Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendous progress in hard- and software of the past decades was an important gateway for developing computerized systems that are able to support decision making on different levels within enterprises. T...

Pavement maintenance optimization model using Markov Decision Processes

Science.gov (United States)

Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

2017-09-01

This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

Application of stochastic optimization to nuclear power plant asset management decisions

International Nuclear Information System (INIS)

Morton, D.; Koc, A.; Hess, S. M.

2013-01-01

We describe the development and application of stochastic optimization models and algorithms to address an issue of critical importance in the strategic allocation of resources; namely, the selection of a portfolio of capital investment projects under the constraints of a limited and uncertain budget. This issue is significant and one that faces decision-makers across all industries. The objective of this strategic decision process is generally self evident - to maximize the value obtained from the portfolio of selected projects (with value usually measured in terms of the portfolio's net present value). However, heretofore, many organizations have developed processes to make these investment decisions using simplistic rule-based rank-ordering schemes. This approach has the significant limitation of not accounting for the (often large) uncertainties in the costs or economic benefits associated with the candidate projects or in the uncertainties in the actual funds available to be expended over the projected period of time. As a result, the simple heuristic approaches that typically are employed in industrial practice generate outcomes that are non-optimal and do not achieve the level of benefits intended. In this paper we describe the results of research performed to utilize stochastic optimization models and algorithms to address this limitation by explicitly incorporating the evaluation of uncertainties in the analysis and decision making process. (authors)

Application of stochastic optimization to nuclear power plant asset management decisions

Energy Technology Data Exchange (ETDEWEB)

Morton, D. [Graduate Program in Operations Research and Industrial Engineering, University of Texas at Austin, Austin, TX, 78712 (United States); Koc, A. [IBM T.J. Watson Research Center, Business Analytics and Mathematical Sciences Dept., 1101 Kitchawan Rd., Yorktown Heights, NY, 10598 (United States); Hess, S. M. [Electric Power Research Institute, 300 Baywood Road, West Chester, PA, 19382 (United States)

2013-07-01

We describe the development and application of stochastic optimization models and algorithms to address an issue of critical importance in the strategic allocation of resources; namely, the selection of a portfolio of capital investment projects under the constraints of a limited and uncertain budget. This issue is significant and one that faces decision-makers across all industries. The objective of this strategic decision process is generally self evident - to maximize the value obtained from the portfolio of selected projects (with value usually measured in terms of the portfolio's net present value). However, heretofore, many organizations have developed processes to make these investment decisions using simplistic rule-based rank-ordering schemes. This approach has the significant limitation of not accounting for the (often large) uncertainties in the costs or economic benefits associated with the candidate projects or in the uncertainties in the actual funds available to be expended over the projected period of time. As a result, the simple heuristic approaches that typically are employed in industrial practice generate outcomes that are non-optimal and do not achieve the level of benefits intended. In this paper we describe the results of research performed to utilize stochastic optimization models and algorithms to address this limitation by explicitly incorporating the evaluation of uncertainties in the analysis and decision making process. (authors)

Road maintenance optimization through a discrete-time semi-Markov decision process

International Nuclear Information System (INIS)

Zhang Xueqing; Gao Hui

2012-01-01

Optimization models are necessary for efficient and cost-effective maintenance of a road network. In this regard, road deterioration is commonly modeled as a discrete-time Markov process such that an optimal maintenance policy can be obtained based on the Markov decision process, or as a renewal process such that an optimal maintenance policy can be obtained based on the renewal theory. However, the discrete-time Markov process cannot capture the real time at which the state transits while the renewal process considers only one state and one maintenance action. In this paper, road deterioration is modeled as a semi-Markov process in which the state transition has the Markov property and the holding time in each state is assumed to follow a discrete Weibull distribution. Based on this semi-Markov process, linear programming models are formulated for both infinite and finite planning horizons in order to derive optimal maintenance policies to minimize the life-cycle cost of a road network. A hypothetical road network is used to illustrate the application of the proposed optimization models. The results indicate that these linear programming models are practical for the maintenance of a road network having a large number of road segments and that they are convenient to incorporate various constraints on the decision process, for example, performance requirements and available budgets. Although the optimal maintenance policies obtained for the road network are randomized stationary policies, the extent of this randomness in decision making is limited. The maintenance actions are deterministic for most states and the randomness in selecting actions occurs only for a few states.

Decision support tools for advanced energy management

International Nuclear Information System (INIS)

Marik, Karel; Schindler, Zdenek; Stluka, Petr

2008-01-01

Rising fuel costs boost energy prices, which is a driving force for improving efficiency of operation of any energy generation facility. This paper focuses on enhancing the operation of distributed integrated energy systems (IES), system that bring together all forms of cooling, heating and power (CCHP) technologies. Described methodology can be applied in power generation and district heating companies, as well as in small-scale systems that supply multiple types of utilities to consumers in industrial, commercial, residential and governmental spheres. Dispatching of such system in an optimal way needs to assess large number of production and purchasing schemes in conditions of continually changing market and variable utility demands influenced by many external factors, very often by weather conditions. The paper describes a combination of forecasting and optimization methods that supports effective decisions in IES system management. The forecaster generates the future most probable utility demand several hours or days ahead, derived from the past energy consumer behaviour. The optimizer generates economically most efficient operating schedule for the IES system that matches these forecasted energy demands and respects expected purchased energy prices. (author)

ADVISHE: A new tool to report validation of health-economic decision models

NARCIS (Netherlands)

Vemer, P.; Corro Ramos, I.; Van Voorn, G.; Al, M.J.; Feenstra, T.L.

2014-01-01

Background: Modelers and reimbursement decision makers could both profit from a more systematic reporting of the efforts to validate health-economic (HE) models. Objectives: Development of a tool to systematically report validation efforts of HE decision models and their outcomes. Methods: A gross

Selection of a tool to decision making for site selection for high level waste

International Nuclear Information System (INIS)

Madeira, J.G.; Alvin, A.C.M.; Martins, V.B.; Monteiro, N.A.

2016-01-01

The aim of this paper is to create a panel comparing some of the key decision-making support tools used in situations with the characteristics of the problem of selecting suitable areas for constructing a final deep geologic repository. The tools addressed in this work are also well known and with easy implementation. The decision-making process in matters of this kind is, in general, complex due to its multi-criteria nature and the conflicting opinions of various stakeholders. Thus, a comprehensive study was performed with the literature in this subject, specifically in documents of the International Atomic Energy Agency (IAEA), regarding the importance of the criteria involved in the decision-making process. Therefore, we highlighted six judgment attributes for selecting a decision support tool, suitable for the problem. For this study, we have selected the following multi-criteria tools: AHP, Delphi, Brainstorm, Nominal Group Technique and AHP-Delphi. Finally, the AHP-Delphi method has demonstrated to be more appropriate for managing the inherent multiple attributes to the problem proposed. (authors)

Optimization and analysis of decision trees and rules: Dynamic programming approach

KAUST Repository

Alkhalid, Abdulaziz

2013-08-01

This paper is devoted to the consideration of software system Dagger created in KAUST. This system is based on extensions of dynamic programming. It allows sequential optimization of decision trees and rules relative to different cost functions, derivation of relationships between two cost functions (in particular, between number of misclassifications and depth of decision trees), and between cost and uncertainty of decision trees. We describe features of Dagger and consider examples of this systems work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction. © 2013 Taylor and Francis Group, LLC.

Optimization and analysis of decision trees and rules: Dynamic programming approach

KAUST Repository

Alkhalid, Abdulaziz; Amin, Talha M.; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

This paper is devoted to the consideration of software system Dagger created in KAUST. This system is based on extensions of dynamic programming. It allows sequential optimization of decision trees and rules relative to different cost functions, derivation of relationships between two cost functions (in particular, between number of misclassifications and depth of decision trees), and between cost and uncertainty of decision trees. We describe features of Dagger and consider examples of this systems work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction. © 2013 Taylor and Francis Group, LLC.

Using Collaborative Simulation Modeling to Develop a Web-Based Tool to Support Policy-Level Decision Making About Breast Cancer Screening Initiation Age

Directory of Open Access Journals (Sweden)

Elizabeth S. Burnside MD, MPH, MS

2017-07-01

Full Text Available Background: There are no publicly available tools designed specifically to assist policy makers to make informed decisions about the optimal ages of breast cancer screening initiation for different populations of US women. Objective: To use three established simulation models to develop a web-based tool called Mammo OUTPuT. Methods: The simulation models use the 1970 US birth cohort and common parameters for incidence, digital screening performance, and treatment effects. Outcomes include breast cancers diagnosed, breast cancer deaths averted, breast cancer mortality reduction, false-positive mammograms, benign biopsies, and overdiagnosis. The Mammo OUTPuT tool displays these outcomes for combinations of age at screening initiation (every year from 40 to 49, annual versus biennial interval, lifetime versus 10-year horizon, and breast density, compared to waiting to start biennial screening at age 50 and continuing to 74. The tool was piloted by decision makers (n = 16 who completed surveys. Results: The tool demonstrates that benefits in the 40s increase linearly with earlier initiation age, without a specific threshold age. Likewise, the harms of screening increase monotonically with earlier ages of initiation in the 40s. The tool also shows users how the balance of benefits and harms varies with breast density. Surveys revealed that 100% of users (16/16 liked the appearance of the site; 94% (15/16 found the tool helpful; and 94% (15/16 would recommend the tool to a colleague. Conclusions: This tool synthesizes a representative subset of the most current CISNET (Cancer Intervention and Surveillance Modeling Network simulation model outcomes to provide policy makers with quantitative data on the benefits and harms of screening women in the 40s. Ultimate decisions will depend on program goals, the population served, and informed judgments about the weight of benefits and harms.

A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge.

Science.gov (United States)

Rahman, M Azizur; Rusteberg, Bernd; Gogu, R C; Lobo Ferreira, J P; Sauter, Martin

2012-05-30

This study reports the development of a new spatial multi-criteria decision analysis (SMCDA) software tool for selecting suitable sites for Managed Aquifer Recharge (MAR) systems. The new SMCDA software tool functions based on the combination of existing multi-criteria evaluation methods with modern decision analysis techniques. More specifically, non-compensatory screening, criteria standardization and weighting, and Analytical Hierarchy Process (AHP) have been combined with Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). This SMCDA tool may be implemented with a wide range of decision maker's preferences. The tool's user-friendly interface helps guide the decision maker through the sequential steps for site selection, those steps namely being constraint mapping, criteria hierarchy, criteria standardization and weighting, and criteria overlay. The tool offers some predetermined default criteria and standard methods to increase the trade-off between ease-of-use and efficiency. Integrated into ArcGIS, the tool has the advantage of using GIS tools for spatial analysis, and herein data may be processed and displayed. The tool is non-site specific, adaptive, and comprehensive, and may be applied to any type of site-selection problem. For demonstrating the robustness of the new tool, a case study was planned and executed at Algarve Region, Portugal. The efficiency of the SMCDA tool in the decision making process for selecting suitable sites for MAR was also demonstrated. Specific aspects of the tool such as built-in default criteria, explicit decision steps, and flexibility in choosing different options were key features, which benefited the study. The new SMCDA tool can be augmented by groundwater flow and transport modeling so as to achieve a more comprehensive approach to the selection process for the best locations of the MAR infiltration basins, as well as the locations of recovery wells and areas of groundwater protection. The new spatial

Development of a prototype clinical decision support tool for osteoporosis disease management: a qualitative study of focus groups

Directory of Open Access Journals (Sweden)

Newton David

2010-07-01

the patient education component of the osteoporosis tool. Suggestions for modifying the tool included the addition of a percentile graph showing patients' 10-year risk for osteoporosis or fractures, and ensuring that the tool takes no more than 5 minutes to complete. Conclusions Focus group data revealed the facilitators and barriers to using the osteoporosis tool at the point of care so that it can be optimized to aid physicians in their clinical decision making.

Second Order Optimality in Markov Decision Chains

Czech Academy of Sciences Publication Activity Database

Sladký, Karel

2017-01-01

Roč. 53, č. 6 (2017), s. 1086-1099 ISSN 0023-5954 R&D Projects: GA ČR GA15-10331S Institutional support: RVO:67985556 Keywords : Markov decision chains * second order optimality * optimalilty conditions for transient, discounted and average models * policy and value iterations Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/E/sladky-0485146.pdf

Particle swarm optimization of driving torque demand decision based on fuel economy for plug-in hybrid electric vehicle

International Nuclear Information System (INIS)

Shen, Peihong; Zhao, Zhiguo; Zhan, Xiaowen; Li, Jingwei

2017-01-01

In this paper, an energy management strategy based on logic threshold is proposed for a plug-in hybrid electric vehicle. The plug-in hybrid electric vehicle powertrain model is established using MATLAB/Simulink based on experimental tests of the power components, which is validated by the comparison with the verified simulation model which is built in the AVL Cruise. The influence of the driving torque demand decision on the fuel economy of plug-in hybrid electric vehicle is studied using a simulation. The optimization method for the driving torque demand decision, which refers to the relationship between the accelerator pedal opening and driving torque demand, from the perspective of fuel economy is formulated. The dynamically changing inertia weight particle swarm optimization is used to optimize the decision parameters. The simulation results show that the optimized driving torque demand decision can improve the PHEV fuel economy by 15.8% and 14.5% in the fuel economy test driving cycle of new European driving cycle and worldwide harmonized light vehicles test respectively, using the same rule-based energy management strategy. The proposed optimization method provides a theoretical guide for calibrating the parameters of driving torque demand decision to improve the fuel economy of the real plug-in hybrid electric vehicle. - Highlights: • The influence of the driving torque demand decision on the fuel economy is studied. • The optimization method for the driving torque demand decision is formulated. • An improved particle swarm optimization is utilized to optimize the parameters. • Fuel economy is improved by using the optimized driving torque demand decision.

Application of the PredictAD Decision Support Tool to a Danish Cohort of Patients with Alzheimer's Disease and Other Dementias

DEFF Research Database (Denmark)

Simonsen, A H; Mattila, J; Hejl, A M

2013-01-01

Background: The diagnosis of Alzheimer's disease (AD) is based on an ever-increasing body of data and knowledge making it a complex task. The PredictAD tool integrates heterogeneous patient data using an interactive user interface to provide decision support. The aim of this project was to invest......Background: The diagnosis of Alzheimer's disease (AD) is based on an ever-increasing body of data and knowledge making it a complex task. The PredictAD tool integrates heterogeneous patient data using an interactive user interface to provide decision support. The aim of this project...... forest. Results: The DSI performed best for this realistic dataset with an accuracy of 76.6% compared to the accuracies for the naïve Bayesian classifier and random forest of 67.4 and 66.7%, respectively. Furthermore, the DSI differentiated between the four diagnostic groups with a p value of ....0001. Conclusion: In this dataset, the DSI method used by the PredictAD tool showed a superior performance for the differentiation between patients with AD and those with other dementias. However, the methods need to be refined further in order to optimize the differential diagnosis between AD, FTD, VaD and DLB....

Simple decision tools to help optimize the control strategy 2 weeks into a Danish FMD epidemic

DEFF Research Database (Denmark)

Willeberg, Preben; Hisham Beshara Halasa, Tariq; Boklund, Anette

2012-01-01

The choice of whether or not to apply emergency vaccination is one of the most difficult decisions facing the authorities when foot-and-mouth disease (FMD) breaks out in a free country (Barnett et al. 2002). A simple quantitative tool has been proposed using the first 14-days incidence (FFI...... detected after day 14, the epidemic duration after day 14 and the size of the affected region at the end of the epidemic. Statistically significant positive correlations were found in all regression analyses of the data. There was, however, a high degree of variation (Fig. 1), which is to be expected...... to estimate predictive values by applying selected cut-off- values for both the dependent and the independent variables (Table 1). Emergency vaccination should be considered during an outbreak if the predicted cumulative size, duration or cost of the epidemic appears alarming (EU 2003, Kitching et al. 2005...

Strategic Risk Assessment: A Decision Tool for Complex Decisions

Energy Technology Data Exchange (ETDEWEB)

Pollard, Simon; Duarte-Davidson, Raquel; Yearsley, Roger [Environment Agency, London (United Kingdom). National Centre for Risk Analysis and Options Appraisal; Kemp, Ray; Crawford, Mark [Galson Sciences Limited, Oakham (United Kingdom)

2001-07-01

Reporting on the state of the environment often requires policy makers and regulators to prioritise a range of diverse environmental issues for the purpose of directing future action on environmental protection and improvement. Information on environmental issues to inform this type of analysis can be disparate, it may be too voluminous or even absent. Data on a range of issues are rarely presented in a common format that allows easy comparison. Nevertheless, strategic judgements are required on the significance of impacts from various environmental pressures and on the inherent uncertainties. Prioritising issues forces a discussion among stakeholders of the relative significance of 'environmental harm' from pressures acting on various receptors in the environment. Discussions of this sort rapidly evolve into a discourse on risks and values. In an attempt to help systematise these discussions and provide practical tools for the analysis of environmental risks at a strategic level, the Environment Agency of England and Wales has initiated developmental research on strategic risk assessment. The tools developed under this research use the concept of 'environmental harm' as a common currency, viewed from technical, social and economic perspectives, to analyse impacts from a range of environmental pressures. Critical to an informed debate is an understanding and analysis both of the various characteristics of harm (spatial and temporal extent, reversibility, latency, etc.) and of the social response to the actual or potential environmental harm. Recent developments in this approach allow a presentation of the analysis in a structured fashion so as to better inform risk management decisions. Here, we present recent developments in the strategic risk assessment research tool, as tested by case studies from state of the environment reporting and the analysis of a regional environmental plan. We discuss its relative advantages and limitations and its

Strategic Risk Assessment: A Decision Tool for Complex Decisions

International Nuclear Information System (INIS)

Pollard, Simon; Duarte-Davidson, Raquel; Yearsley, Roger

2001-01-01

Reporting on the state of the environment often requires policy makers and regulators to prioritise a range of diverse environmental issues for the purpose of directing future action on environmental protection and improvement. Information on environmental issues to inform this type of analysis can be disparate, it may be too voluminous or even absent. Data on a range of issues are rarely presented in a common format that allows easy comparison. Nevertheless, strategic judgements are required on the significance of impacts from various environmental pressures and on the inherent uncertainties. Prioritising issues forces a discussion among stakeholders of the relative significance of 'environmental harm' from pressures acting on various receptors in the environment. Discussions of this sort rapidly evolve into a discourse on risks and values. In an attempt to help systematise these discussions and provide practical tools for the analysis of environmental risks at a strategic level, the Environment Agency of England and Wales has initiated developmental research on strategic risk assessment. The tools developed under this research use the concept of 'environmental harm' as a common currency, viewed from technical, social and economic perspectives, to analyse impacts from a range of environmental pressures. Critical to an informed debate is an understanding and analysis both of the various characteristics of harm (spatial and temporal extent, reversibility, latency, etc.) and of the social response to the actual or potential environmental harm. Recent developments in this approach allow a presentation of the analysis in a structured fashion so as to better inform risk management decisions. Here, we present recent developments in the strategic risk assessment research tool, as tested by case studies from state of the environment reporting and the analysis of a regional environmental plan. We discuss its relative advantages and limitations and its wider potential role

Risk analysis as a decision tool

International Nuclear Information System (INIS)

Yadigaroglu, G.; Chakraborty, S.

1985-01-01

From 1983 - 1985 a lecture series entitled ''Risk-benefit analysis'' was held at the Swiss Federal Institute of Technology (ETH), Zurich, in cooperation with the Central Department for the Safety of Nuclear Installations of the Swiss Federal Agency of Energy Economy. In that setting the value of risk-oriented evaluation models as a decision tool in safety questions was discussed on a broad basis. Experts of international reputation from the Federal Republic of Germany, France, Canada, the United States and Switzerland have contributed to report in this joint volume on the uses of such models. Following an introductory synopsis on risk analysis and risk assessment the book deals with practical examples in the fields of medicine, nuclear power, chemistry, transport and civil engineering. Particular attention is paid to the dialogue between analysts and decision makers taking into account the economic-technical aspects and social values. The recent chemical disaster in the Indian city of Bhopal again signals the necessity of such analyses. All the lectures were recorded individually. (orig./HP) [de

Learning decision trees with flexible constraints and objectives using integer optimization

NARCIS (Netherlands)

Verwer, S.; Zhang, Y.

2017-01-01

We encode the problem of learning the optimal decision tree of a given depth as an integer optimization problem. We show experimentally that our method (DTIP) can be used to learn good trees up to depth 5 from data sets of size up to 1000. In addition to being efficient, our new formulation allows

Optimal condition-based maintenance decisions for systems with dependent stochastic degradation of components

International Nuclear Information System (INIS)

Hong, H.P.; Zhou, W.; Zhang, S.; Ye, W.

2014-01-01

Components in engineered systems are subjected to stochastic deterioration due to the operating environmental conditions, and the uncertainty in material properties. The components need to be inspected and possibly replaced based on preventive or failure replacement criteria to provide the intended and safe operation of the system. In the present study, we investigate the influence of dependent stochastic degradation of multiple components on the optimal maintenance decisions. We use copula to model the dependent stochastic degradation of components, and formulate the optimal decision problem based on the minimum expected cost rule and the stochastic dominance rules. The latter is used to cope with decision maker's risk attitude. We illustrate the developed probabilistic analysis approach and the influence of the dependency of the stochastic degradation on the preferred decisions through numerical examples

Integrated Decision Tools for Sustainable Watershed/Ground Water and Crop Health using Predictive Weather, Remote Sensing, and Irrigation Decision Tools

Science.gov (United States)

Jones, A. S.; Andales, A.; McGovern, C.; Smith, G. E. B.; David, O.; Fletcher, S. J.

2017-12-01

US agricultural and Govt. lands have a unique co-dependent relationship, particularly in the Western US. More than 30% of all irrigated US agricultural output comes from lands sustained by the Ogallala Aquifer in the western Great Plains. Six US Forest Service National Grasslands reside within the aquifer region, consisting of over 375,000 ha (3,759 km2) of USFS managed lands. Likewise, National Forest lands are the headwaters to many intensive agricultural regions. Our Ogallala Aquifer team is enhancing crop irrigation decision tools with predictive weather and remote sensing data to better manage water for irrigated crops within these regions. An integrated multi-model software framework is used to link irrigation decision tools, resulting in positive management benefits on natural water resources. Teams and teams-of-teams can build upon these multi-disciplinary multi-faceted modeling capabilities. For example, the CSU Catalyst for Innovative Partnerships program has formed a new multidisciplinary team that will address "Rural Wealth Creation" focusing on the many integrated links between economic, agricultural production and management, natural resource availabilities, and key social aspects of govt. policy recommendations. By enhancing tools like these with predictive weather and other related data (like in situ measurements, hydrologic models, remotely sensed data sets, and (in the near future) linking to agro-economic and life cycle assessment models) this work demonstrates an integrated data-driven future vision of inter-meshed dynamic systems that can address challenging multi-system problems. We will present the present state of the work and opportunities for future involvement.

Designing a data-driven decision support tool for nurse scheduling in the emergency department: a case study of a southern New Jersey emergency department.

Science.gov (United States)

Otegbeye, Mojisola; Scriber, Roslyn; Ducoin, Donna; Glasofer, Amy

2015-01-01

A health system serving Burlington and Camden Counties, New Jersey, sought to improve labor productivity for its emergency departments, with emphasis on optimizing nursing staff schedules. Using historical emergency department visit data and operating constraints, a decision support tool was designed to recommend the number of emergency nurses needed in each hour for each day of the week. The pilot emergency department nurse managers used the decision support tool's recommendations to redeploy nurse hours from weekends into a float pool to support periods of demand spikes on weekdays. Productivity improved significantly, with no unfavorable impact on patient throughput, and patient and staff satisfaction. Today's emergency department manager can leverage the increasing ease of access to the emergency department information system's data repository to successfully design a simple but effective tool to support the alignment of its nursing schedule with demand patterns. Copyright © 2015 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.

A Query Cache Tool for Optimizing Repeatable and Parallel OLAP Queries

Science.gov (United States)

Santos, Ricardo Jorge; Bernardino, Jorge

On-line analytical processing against data warehouse databases is a common form of getting decision making information for almost every business field. Decision support information oftenly concerns periodic values based on regular attributes, such as sales amounts, percentages, most transactioned items, etc. This means that many similar OLAP instructions are periodically repeated, and simultaneously, between the several decision makers. Our Query Cache Tool takes advantage of previously executed queries, storing their results and the current state of the data which was accessed. Future queries only need to execute against the new data, inserted since the queries were last executed, and join these results with the previous ones. This makes query execution much faster, because we only need to process the most recent data. Our tool also minimizes the execution time and resource consumption for similar queries simultaneously executed by different users, putting the most recent ones on hold until the first finish and returns the results for all of them. The stored query results are held until they are considered outdated, then automatically erased. We present an experimental evaluation of our tool using a data warehouse based on a real-world business dataset and use a set of typical decision support queries to discuss the results, showing a very high gain in query execution time.

System and method for integrating hazard-based decision making tools and processes

Science.gov (United States)

Hodgin, C Reed [Westminster, CO

2012-03-20

A system and method for inputting, analyzing, and disseminating information necessary for identified decision-makers to respond to emergency situations. This system and method provides consistency and integration among multiple groups, and may be used for both initial consequence-based decisions and follow-on consequence-based decisions. The system and method in a preferred embodiment also provides tools for accessing and manipulating information that are appropriate for each decision-maker, in order to achieve more reasoned and timely consequence-based decisions. The invention includes processes for designing and implementing a system or method for responding to emergency situations.

Pilot study of a point-of-use decision support tool for cancer clinical trials eligibility.

Science.gov (United States)

Breitfeld, P P; Weisburd, M; Overhage, J M; Sledge, G; Tierney, W M

1999-01-01

Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites.

Dimensions of design space: a decision-theoretic approach to optimal research design.

Science.gov (United States)

Conti, Stefano; Claxton, Karl

2009-01-01

Bayesian decision theory can be used not only to establish the optimal sample size and its allocation in a single clinical study but also to identify an optimal portfolio of research combining different types of study design. Within a single study, the highest societal payoff to proposed research is achieved when its sample sizes and allocation between available treatment options are chosen to maximize the expected net benefit of sampling (ENBS). Where a number of different types of study informing different parameters in the decision problem could be conducted, the simultaneous estimation of ENBS across all dimensions of the design space is required to identify the optimal sample sizes and allocations within such a research portfolio. This is illustrated through a simple example of a decision model of zanamivir for the treatment of influenza. The possible study designs include: 1) a single trial of all the parameters, 2) a clinical trial providing evidence only on clinical endpoints, 3) an epidemiological study of natural history of disease, and 4) a survey of quality of life. The possible combinations, samples sizes, and allocation between trial arms are evaluated over a range of cost-effectiveness thresholds. The computational challenges are addressed by implementing optimization algorithms to search the ENBS surface more efficiently over such large dimensions.

Inverse Optimization and Forecasting Techniques Applied to Decision-making in Electricity Markets

DEFF Research Database (Denmark)

Saez Gallego, Javier

patterns that the load traditionally exhibited. On the other hand, this thesis is motivated by the decision-making processes of market players. In response to these challenges, this thesis provides mathematical models for decision-making under uncertainty in electricity markets. Demand-side bidding refers......This thesis deals with the development of new mathematical models that support the decision-making processes of market players. It addresses the problems of demand-side bidding, price-responsive load forecasting and reserve determination. From a methodological point of view, we investigate a novel...... approach to model the response of aggregate price-responsive load as a constrained optimization model, whose parameters are estimated from data by using inverse optimization techniques. The problems tackled in this dissertation are motivated, on one hand, by the increasing penetration of renewable energy...

Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.

Science.gov (United States)

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2014-09-01

Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.

System Sketch: A Visualization Tool to Improve Community Decision Making

Science.gov (United States)

Making decisions in coastal and estuarine management requires a comprehensive understanding of the linkages between environmental, social, and economic systems. SystemSketch is a web-based scoping tool designed to assist resource managers in characterizing their systems, explorin...

Clarity versus complexity: land-use modeling as a practical tool for decision-makers

Science.gov (United States)

Sohl, Terry L.; Claggett, Peter

2013-01-01

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

A modeling framework for optimal long-term care insurance purchase decisions in retirement planning.

Science.gov (United States)

Gupta, Aparna; Li, Lepeng

2004-05-01

The level of need and costs of obtaining long-term care (LTC) during retired life require that planning for it is an integral part of retirement planning. In this paper, we divide retirement planning into two phases, pre-retirement and post-retirement. On the basis of four interrelated models for health evolution, wealth evolution, LTC insurance premium and coverage, and LTC cost structure, a framework for optimal LTC insurance purchase decisions in the pre-retirement phase is developed. Optimal decisions are obtained by developing a trade-off between post-retirement LTC costs and LTC insurance premiums and coverage. Two-way branching models are used to model stochastic health events and asset returns. The resulting optimization problem is formulated as a dynamic programming problem. We compare the optimal decision under two insurance purchase scenarios: one assumes that insurance is purchased for good and other assumes it may be purchased, relinquished and re-purchased. Sensitivity analysis is performed for the retirement age.

Optimal Guaranteed Service Time and Service Level Decision with Time and Service Level Sensitive Demand

Directory of Open Access Journals (Sweden)

Sangjun Park

2014-01-01

Full Text Available We consider a two-stage supply chain with one supplier and one retailer. The retailer sells a product to customer and the supplier provides a product in a make-to-order mode. In this case, the supplier’s decisions on service time and service level and the retailer’s decision on retail price have effects on customer demand. We develop optimization models to determine the optimal retail price, the optimal guaranteed service time, the optimal service level, and the optimal capacity to maximize the expected profit of the whole supply chain. The results of numerical experiments show that it is more profitable to determine the optimal price, the optimal guaranteed service time, and the optimal service level simultaneously and the proposed model is more profitable in service level sensitive market.

SOLVING OPTIMAL ASSEMBLY LINE CONFIGURATION TASK BY MULTIOBJECTIVE DECISION MAKING METHODS

Directory of Open Access Journals (Sweden)

Ján ČABALA

2017-06-01

Full Text Available This paper deals with looking for the optimal configuration of automated assembly line model placed within Department of Cybernetics and Artificial Intelligence (DCAI. In order to solve this problem, Stateflow model of each configuration was created to simulate the behaviour of particular assembly line configuration. Outputs from these models were used as inputs into the multiobjective decision making process. Multi-objective decision-making methods were subsequently used to find the optimal configuration of assembly line. Paper describes the whole process of solving this task, from building the models to choosing the best configuration. Specifically, the problem was resolved using the experts’ evaluation method for evaluating the weights of every decision-making criterion, while the ELECTRE III, TOPSIS and AGREPREF methods were used for ordering the possible solutions from the most to the least suitable alternative. Obtained results were compared and final solution of this multi-objective decisionmaking problem is chosen.

An open-source optimization tool for solar home systems: A case study in Namibia

International Nuclear Information System (INIS)

Campana, Pietro Elia; Holmberg, Aksel; Pettersson, Oscar; Klintenberg, Patrik; Hangula, Abraham; Araoz, Fabian Benavente; Zhang, Yang; Stridh, Bengt; Yan, Jinyue

2016-01-01

Highlights: • An open-source optimization tool for solar home systems (SHSs) design is developed. • The optimization tool is written in MS Excel-VBA. • The optimization tool is validated with a commercial and open-source software. • The optimization tool has the potential of improving future SHS installations. - Abstract: Solar home systems (SHSs) represent a viable technical solution for providing electricity to households and improving standard of living conditions in areas not reached by the national grid or local grids. For this reason, several rural electrification programmes in developing countries, including Namibia, have been relying on SHSs to electrify rural off-grid communities. However, the limited technical know-how of service providers, often resulting in over- or under-sized SHSs, is an issue that has to be solved to avoid dissatisfaction of SHSs’ users. The solution presented here is to develop an open-source software that service providers can use to optimally design SHSs components based on the specific electricity requirements of the end-user. The aim of this study is to develop and validate an optimization model written in MS Excel-VBA which calculates the optimal SHSs components capacities guaranteeing the minimum costs and the maximum system reliability. The results obtained with the developed tool showed good agreement with a commercial software and a computational code used in research activities. When applying the developed optimization tool to existing systems, the results identified that several components were incorrectly sized. The tool has thus the potentials of improving future SHSs installations, contributing to increasing satisfaction of end-users.

Interactive Decision-Support Tool for Risk-Based Radiation Therapy Plan Comparison for Hodgkin Lymphoma

DEFF Research Database (Denmark)

Brodin, N. Patrik; Maraldo, Maja V.; Aznar, Marianne C.

2014-01-01

PURPOSE: To present a novel tool that allows quantitative estimation and visualization of the risk of various relevant normal tissue endpoints to aid in treatment plan comparison and clinical decision making in radiation therapy (RT) planning for Hodgkin lymphoma (HL). METHODS AND MATERIALS...... and a volumetric modulated arc therapy plan for a patient with mediastinal HL. CONCLUSION: This multiple-endpoint decision-support tool provides quantitative risk estimates to supplement the clinical judgment of the radiation oncologist when comparing different RT options....... of dose-response curves to drive the reoptimization of a volumetric modulated arc therapy treatment plan for an HL patient with head-and-neck involvement. We also use this decision-support tool to visualize and quantitatively evaluate the trade-off between a 3-dimensional conformal RT plan...

A Debate and Decision-Making Tool for Enhanced Learning

Science.gov (United States)

López Garcia, Diego A.; Mateo Sanguino, Tomás de J.; Cortés Ancos, Estefania; Fernández de Viana González, Iñaki

2016-01-01

Debates have been used to develop critical thinking within teaching environments. Many learning activities are configured as working groups, which use debates to make decisions. Nevertheless, in a classroom debate, only a few students can participate; large work groups are similarly limited. Whilst the use of web tools would appear to offer a…

Portfolio Management Decision Support Tools Analysis Relating to Management Value Metrics

National Research Council Canada - National Science Library

Goodson, Christopher J; Knutson, Richard D

2007-01-01

.... The results of this research will assist MDA managers, and operational leaders, in making portfolio management decisions for allocating resources to create the correct support tools for MDA processes...

Application of goal programming to decision problem on optimal allocation of radiation workers

International Nuclear Information System (INIS)

Sa, Sangduk; Narita, Masakuni

1993-01-01

This paper is concerned with an optimal planning in a multiple objective decision-making problem of allocating radiation workers to workplaces associated with occupational exposure. The model problem is formulated with the application of goal programming which effectively followed up diverse and conflicting factors influencing the optimal decision. The formulation is based on the data simulating the typical situations encountered at the operating facilities such as nuclear power plants where exposure control is critical to the management. Multiple goals set by the decision-maker/manager who has the operational responsibilities for radiological protection are illustrated in terms of work requirements, exposure constraints of the places, desired allocation of specific personnel and so on. Test results of the model are considered to indicate that the model structure and its solution process can provide the manager with a good set of analysis of his problems in implementing the optimization review of radiation protection during normal operation. (author)

Particle swarm as optimization tool in complex nuclear engineering problems

International Nuclear Information System (INIS)

Medeiros, Jose Antonio Carlos Canedo

2005-06-01

Due to its low computational cost, gradient-based search techniques associated to linear programming techniques are being used as optimization tools. These techniques, however, when applied to multimodal search spaces, can lead to local optima. When finding solutions for complex multimodal domains, random search techniques are being used with great efficacy. In this work we exploit the swarm optimization algorithm search power capacity as an optimization tool for the solution of complex high dimension and multimodal search spaces of nuclear problems. Due to its easy and natural representation of high dimension domains, the particle swarm optimization was applied with success for the solution of complex nuclear problems showing its efficacy in the search of solutions in high dimension and complex multimodal spaces. In one of these applications it enabled a natural and trivial solution in a way not obtained with other methods confirming the validity of its application. (author)

Constructing an optimal decision tree for FAST corner point detection

KAUST Repository

Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail

2011-01-01

In this paper, we consider a problem that is originated in computer vision: determining an optimal testing strategy for the corner point detection problem that is a part of FAST algorithm [11,12]. The problem can be formulated as building a decision tree with the minimum average depth for a decision table with all discrete attributes. We experimentally compare performance of an exact algorithm based on dynamic programming and several greedy algorithms that differ in the attribute selection criterion. © 2011 Springer-Verlag.

Guidance Tools for Use in Nuclear Material Management Decisions Making

Energy Technology Data Exchange (ETDEWEB)

Johnson, G. V.; Baker, D. J.; Sorenson, K. B.; Boeke, S. G.

2002-02-26

This paper describes the results of Recommendation 14 of the Integrated Nuclear Materials Management Plan (INMMP) which was the product of a management initiative at the highest levels of the Department of Energy responding to a congressional directive to accelerate the work of achieving integration and cutting long-term costs associated with the management of nuclear materials, with the principal focus on excess materials. The INMMP provided direction to ''Develop policy-level decision support tools to support long-term planning and decision making.'' To accomplish this goal a team from the Savannah River Site, Sandia National Laboratories, Idaho National Engineering and Environmental Laboratory (INEEL), and the U.S. Department of Energy experienced in the decision-making process developed a Guidebook to Decision-Making Methods. The goal of the team organized to implement Recommendation 14 was to instill transparency, consistency, rigor, and discipline in the DOE decision process. The guidebook introduces a process and a selection of proven methods for disciplined decision-making so that the results are clearer, more transparent, and easier for reviewers to understand and accept. It was written to set a standard for a consistent decision process.

Updating Optimal Decisions Using Game Theory and Exploring Risk Behavior Through Response Surface Methodology

National Research Council Canada - National Science Library

Jordan, Jeremy D

2007-01-01

.... Methodology is developed that allows a decision maker to change his perceived optimal policy based on available knowledge of the opponents strategy, where the opponent is a rational decision maker...

Pareto frontier analyses based decision making tool for transportation of hazardous waste

International Nuclear Information System (INIS)

Das, Arup; Mazumder, T.N.; Gupta, A.K.

2012-01-01

Highlights: ► Posteriori method using multi-objective approach to solve bi-objective routing problem. ► System optimization (with multiple source–destination pairs) in a capacity constrained network using non-dominated sorting. ► Tools like cost elasticity and angle based focus used to analyze Pareto frontier to aid stakeholders make informed decisions. ► A real life case study of Kolkata Metropolitan Area to explain the workability of the model. - Abstract: Transportation of hazardous wastes through a region poses immense threat on the development along its road network. The risk to the population, exposed to such activities, has been documented in the past. However, a comprehensive framework for routing hazardous wastes has often been overlooked. A regional Hazardous Waste Management scheme should incorporate a comprehensive framework for hazardous waste transportation. This framework would incorporate the various stakeholders involved in decision making. Hence, a multi-objective approach is required to safeguard the interest of all the concerned stakeholders. The objective of this study is to design a methodology for routing of hazardous wastes between the generating units and the disposal facilities through a capacity constrained network. The proposed methodology uses posteriori method with multi-objective approach to find non-dominated solutions for the system consisting of multiple origins and destinations. A case study of transportation of hazardous wastes in Kolkata Metropolitan Area has also been provided to elucidate the methodology.

Modeling decision making as a support tool for policy making on renewable energy development

International Nuclear Information System (INIS)

Cannemi, Marco; García-Melón, Mónica; Aragonés-Beltrán, Pablo; Gómez-Navarro, Tomás

2014-01-01

This paper presents the findings of a study on decision making models for the analysis of capital-risk investors’ preferences on biomass power plants projects. The aim of the work is to improve the support tools for policy makers in the field of renewable energy development. Analytic Network Process (ANP) helps to better understand capital-risk investors preferences towards different kinds of biomass fueled power plants. The results of the research allow public administration to better foresee the investors’ reaction to the incentive system, or to modify the incentive system to better drive investors’ decisions. Changing the incentive system is seen as major risk by investors. Therefore, public administration must design better and longer-term incentive systems, forecasting market reactions. For that, two scenarios have been designed, one showing a typical decision making process and another proposing an improved decision making scenario. A case study conducted in Italy has revealed that ANP allows understanding how capital-risk investors interpret the situation and make decisions when investing on biomass power plants; the differences between the interests of public administrations’s and promoters’, how decision making could be influenced by adding new decision criteria, and which case would be ranked best according to the decision models. - Highlights: • We applied ANP to the investors’ preferences on biomass power plants projects. • The aim is to improve the advising tools for renewable energy policy making. • A case study has been carried out with the help of two experts. • We designed two scenarios: decision making as it is and how could it be improved. • Results prove ANP is a fruitful tool enhancing participation and transparency

Decision support tool for diagnosing the source of variation

Science.gov (United States)

Masood, Ibrahim; Azrul Azhad Haizan, Mohamad; Norbaya Jumali, Siti; Ghazali, Farah Najihah Mohd; Razali, Hazlin Syafinaz Md; Shahir Yahya, Mohd; Azlan, Mohd Azwir bin

2017-08-01

Identifying the source of unnatural variation (SOV) in manufacturing process is essential for quality control. The Shewhart control chart patterns (CCPs) are commonly used to monitor the SOV. However, a proper interpretation of CCPs associated to its SOV requires a high skill industrial practitioner. Lack of knowledge in process engineering will lead to erroneous corrective action. The objective of this study is to design the operating procedures of computerized decision support tool (DST) for process diagnosis. The DST is an embedded tool in CCPs recognition scheme. Design methodology involves analysis of relationship between geometrical features, manufacturing process and CCPs. The DST contents information about CCPs and its possible root cause error and description on SOV phenomenon such as process deterioration in tool bluntness, offsetting tool, loading error, and changes in materials hardness. The DST will be useful for an industrial practitioner in making effective troubleshooting.

LCA-IWM: A decision support tool for sustainability assessment of waste management systems

International Nuclear Information System (INIS)

Boer, J. den; Boer, E. den; Jager, J.

2007-01-01

The paper outlines the most significant result of the project 'The use of life cycle assessment tools for the development of integrated waste management strategies for cities and regions with rapid growing economies', which was the development of two decision-support tools: a municipal waste prognostic tool and a waste management system assessment tool. The article focuses on the assessment tool, which supports the adequate decision making in the planning of urban waste management systems by allowing the creation and comparison of different scenarios, considering three basic subsystems: (i) temporary storage; (ii) collection and transport and (iii) treatment, disposal and recycling. The design and analysis options, as well as the assumptions made for each subsystem, are shortly introduced, providing an overview of the applied methodologies and technologies. The sustainability assessment methodology used in the project to support the selection of the most adequate scenario is presented with a brief explanation of the procedures, criteria and indicators applied on the evaluation of each of the three sustainability pillars

The development of an online decision support tool for organizational readiness for change.

Science.gov (United States)

Khan, Sobia; Timmings, Caitlyn; Moore, Julia E; Marquez, Christine; Pyka, Kasha; Gheihman, Galina; Straus, Sharon E

2014-05-10

Much importance has been placed on assessing readiness for change as one of the earliest steps of implementation, but measuring it can be a complex and daunting task. Organizations and individuals struggle with how to reliably and accurately measure readiness for change. Several measures have been developed to help organizations assess readiness, but these are often underused due to the difficulty of selecting the right measure. In response to this challenge, we will develop and test a prototype of a decision support tool that is designed to guide individuals interested in implementation in the selection of an appropriate readiness assessment measure for their setting. A multi-phase approach will be used to develop the decision support tool. First, we will identify key measures for assessing organizational readiness for change from a recently completed systematic review. Included measures will be those developed for healthcare settings (e.g., acute care, public health, mental health) and that have been deemed valid and reliable. Second, study investigators and field experts will engage in a mapping exercise to categorize individual items of included measures according to key readiness constructs from an existing framework. Third, a stakeholder panel will be recruited and consulted to determine the feasibility and relevance of the selected measures using a modified Delphi process. Fourth, findings from the mapping exercise and stakeholder consultation will inform the development of a decision support tool that will guide users in appropriately selecting change readiness measures. Fifth, the tool will undergo usability testing. Our proposed decision support tool will address current challenges in the field of organizational change readiness by aiding individuals in selecting a valid and reliable assessment measure that is relevant to user needs and practice settings. We anticipate that implementers and researchers who use our tool will be more likely to conduct

Total Path Length and Number of Terminal Nodes for Decision Trees

KAUST Repository

Hussain, Shahid

2014-01-01

This paper presents a new tool for study of relationships between total path length (average depth) and number of terminal nodes for decision trees. These relationships are important from the point of view of optimization of decision trees

Development of a shared decision-making tool to assist patients and clinicians with decisions on oral anticoagulant treatment for atrial fibrillation.

Science.gov (United States)

Kaiser, Karen; Cheng, Wendy Y; Jensen, Sally; Clayman, Marla L; Thappa, Andrew; Schwiep, Frances; Chawla, Anita; Goldberger, Jeffrey J; Col, Nananda; Schein, Jeff

2015-12-01

Decision aids (DAs) are increasingly used to operationalize shared decision-making (SDM) but their development is not often described. Decisions about oral anticoagulants (OACs) for atrial fibrillation (AF) involve a trade-off between lowering stroke risk and increasing OAC-associated bleeding risk, and consideration of how treatment affects lifestyle. The benefits and risks of OACs hinge upon a patient's risk factors for stroke and bleeding and how they value these outcomes. We present the development of a DA about AF that estimates patients' risks for stroke and bleeding and assesses their preferences for outcomes. Based on a literature review and expert discussions, we identified stroke and major bleeding risk prediction models and embedded them into risk assessment modules. We identified the most important factors in choosing OAC treatment (warfarin used as the default reference OAC) through focus group discussions with AF patients who had used warfarin and clinician interviews. We then designed preference assessment and introductory modules accordingly. We integrated these modules into a prototype AF SDM tool and evaluated its usability through interviews. Our tool included four modules: (1) introduction to AF and OAC treatment risks and benefits; (2) stroke risk assessment; (3) bleeding risk assessment; and (4) preference assessment. Interactive risk calculators estimated patient-specific stroke and bleeding risks; graphics were developed to communicate these risks. After cognitive interviews, the content was improved. The final AF tool calculates patient-specific risks and benefits of OAC treatment and couples these estimates with patient preferences to improve clinical decision-making. The AF SDM tool may help patients choose whether OAC treatment is best for them and represents a patient-centered, integrative approach to educate patients on the benefits and risks of OAC treatment. Future research is needed to evaluate this tool in a real-world setting. The

DECIDE: a Decision Support Tool to Facilitate Parents' Choices Regarding Genome-Wide Sequencing.

Science.gov (United States)

Birch, Patricia; Adam, S; Bansback, N; Coe, R R; Hicklin, J; Lehman, A; Li, K C; Friedman, J M

2016-12-01

We describe the rationale, development, and usability testing for an integrated e-learning tool and decision aid for parents facing decisions about genome-wide sequencing (GWS) for their children with a suspected genetic condition. The online tool, DECIDE, is designed to provide decision-support and to promote high quality decisions about undergoing GWS with or without return of optional incidental finding results. DECIDE works by integrating educational material with decision aids. Users may tailor their learning by controlling both the amount of information and its format - text and diagrams and/or short videos. The decision aid guides users to weigh the importance of various relevant factors in their own lives and circumstances. After considering the pros and cons of GWS and return of incidental findings, DECIDE summarizes the user's responses and apparent preferred choices. In a usability study of 16 parents who had already chosen GWS after conventional genetic counselling, all participants found DECIDE to be helpful. Many would have been satisfied to use it alone to guide their GWS decisions, but most would prefer to have the option of consulting a health care professional as well to aid their decision. Further testing is necessary to establish the effectiveness of using DECIDE as an adjunct to or instead of conventional pre-test genetic counselling for clinical genome-wide sequencing.

Topology and boundary shape optimization as an integrated design tool

Science.gov (United States)

Bendsoe, Martin Philip; Rodrigues, Helder Carrico

1990-01-01

The optimal topology of a two dimensional linear elastic body can be computed by regarding the body as a domain of the plane with a high density of material. Such an optimal topology can then be used as the basis for a shape optimization method that computes the optimal form of the boundary curves of the body. This results in an efficient and reliable design tool, which can be implemented via common FEM mesh generator and CAD type input-output facilities.

Pregnancy outcomes in Ghana : Relavance of clinical decision making support tools for frontline providers of care

OpenAIRE

Amoakoh-Coleman, M.

2016-01-01

Ghana’s slow progress towards attaining millennium development goal 5 has been associated with gaps in quality of care, particularly quality of clinical decision making for clients. This thesis reviews the relevance and effect of clinical decision making support tools on pregnancy outcomes. Relevance of three clinical decision making support tools available to frontline providers of care in the Greater Accra region is discussed. These are routine maternal health service delivery data populati...

Development and Application of a Tool for Optimizing Composite Matrix Viscoplastic Material Parameters

Science.gov (United States)

Murthy, Pappu L. N.; Naghipour Ghezeljeh, Paria; Bednarcyk, Brett A.

2018-01-01

This document describes a recently developed analysis tool that enhances the resident capabilities of the Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) and its application. MAC/GMC is a composite material and laminate analysis software package developed at NASA Glenn Research Center. The primary focus of the current effort is to provide a graphical user interface (GUI) capability that helps users optimize highly nonlinear viscoplastic constitutive law parameters by fitting experimentally observed/measured stress-strain responses under various thermo-mechanical conditions for braided composites. The tool has been developed utilizing the MATrix LABoratory (MATLAB) (The Mathworks, Inc., Natick, MA) programming language. Illustrative examples shown are for a specific braided composite system wherein the matrix viscoplastic behavior is represented by a constitutive law described by seven parameters. The tool is general enough to fit any number of experimentally observed stress-strain responses of the material. The number of parameters to be optimized, as well as the importance given to each stress-strain response, are user choice. Three different optimization algorithms are included: (1) Optimization based on gradient method, (2) Genetic algorithm (GA) based optimization and (3) Particle Swarm Optimization (PSO). The user can mix and match the three algorithms. For example, one can start optimization with either 2 or 3 and then use the optimized solution to further fine tune with approach 1. The secondary focus of this paper is to demonstrate the application of this tool to optimize/calibrate parameters for a nonlinear viscoplastic matrix to predict stress-strain curves (for constituent and composite levels) at different rates, temperatures and/or loading conditions utilizing the Generalized Method of Cells. After preliminary validation of the tool through comparison with experimental results, a detailed virtual parametric study is

Development of an investment decision tool for aged nuclear power plants under uncertainty

International Nuclear Information System (INIS)

Takashima, Ryuta; Nagano, Koji

2010-01-01

The nuclear power generating stock in Japan, which provides 30% or more of the nationwide electricity supply in recent years, is heading into the era of plant aging as those units over 40 years of operation emerge in 2010 and onward. Under accumulating uncertainties surrounding investment decisions, one of the key questions is how best to manage the existing capacity by choosing a wisest option among dismantling, refurbishment, and replacement. This report attempts to develop a methodology to analyze investment decision on aged nuclear units based on real-option analysis, and then presents illustrative simulation runs to demonstrate functions of the numerical models. Major findings are summarized as follows: a) When compared with the conventional net present value (NPV) method, the proposed model is capable to deal with uncertainty explicitly by taking volatility in the formula. Also, for the replacement option, one can choose optimal timings of the dismantling the new plant independently. b) As the profitability increases, the model suggests different investment option as optimal, starting from dismantling to replacement, further to refurbishment, and again to replacement as the most basic pattern. Additionally, where two of the strategies have similar values, postponement of both decisions can be optimal. Through these exercises, the proposed methodology proved itself capable for raising valuable implications to investment decisions in managing the production fleet. (author)

Metabolic engineering with systems biology tools to optimize production of prokaryotic secondary metabolites

DEFF Research Database (Denmark)

Kim, Hyun Uk; Charusanti, Pep; Lee, Sang Yup

2016-01-01

Metabolic engineering using systems biology tools is increasingly applied to overproduce secondary metabolites for their potential industrial production. In this Highlight, recent relevant metabolic engineering studies are analyzed with emphasis on host selection and engineering approaches...... for the optimal production of various prokaryotic secondary metabolites: native versus heterologous hosts (e.g., Escherichia coli) and rational versus random approaches. This comparative analysis is followed by discussions on systems biology tools deployed in optimizing the production of secondary metabolites....... The potential contributions of additional systems biology tools are also discussed in the context of current challenges encountered during optimization of secondary metabolite production....

Implementing of the multi-objective particle swarm optimizer and fuzzy decision-maker in exergetic, exergoeconomic and environmental optimization of a benchmark cogeneration system

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn; Babaie, Meisam; Farmani, Mohammad Reza

2011-01-01

Multi-objective optimization for design of a benchmark cogeneration system namely as the CGAM cogeneration system is performed. In optimization approach, Exergetic, Exergoeconomic and Environmental objectives are considered, simultaneously. In this regard, the set of Pareto optimal solutions known as the Pareto frontier is obtained using the MOPSO (multi-objective particle swarm optimizer). The exergetic efficiency as an exergetic objective is maximized while the unit cost of the system product and the cost of the environmental impact respectively as exergoeconomic and environmental objectives are minimized. Economic model which is utilized in the exergoeconomic analysis is built based on both simple model (used in original researches of the CGAM system) and the comprehensive modeling namely as TTR (total revenue requirement) method (used in sophisticated exergoeconomic analysis). Finally, a final optimal solution from optimal set of the Pareto frontier is selected using a fuzzy decision-making process based on the Bellman-Zadeh approach and results are compared with corresponding results obtained in a traditional decision-making process. Further, results are compared with the corresponding performance of the base case CGAM system and optimal designs of previous works and discussed. -- Highlights: → A multi-objective optimization approach has been implemented in optimization of a benchmark cogeneration system. → Objective functions based on the environmental impact evaluation, thermodynamic and economic analysis are obtained and optimized. → Particle swarm optimizer implemented and its robustness is compared with NSGA-II. → A final optimal configuration is found using various decision-making approaches. → Results compared with previous works in the field.

Generalized concavity in fuzzy optimization and decision analysis

CERN Document Server

Ramík, Jaroslav

2002-01-01

Convexity of sets in linear spaces, and concavity and convexity of functions, lie at the root of beautiful theoretical results that are at the same time extremely useful in the analysis and solution of optimization problems, including problems of either single objective or multiple objectives. Not all of these results rely necessarily on convexity and concavity; some of the results can guarantee that each local optimum is also a global optimum, giving these methods broader application to a wider class of problems. Hence, the focus of the first part of the book is concerned with several types of generalized convex sets and generalized concave functions. In addition to their applicability to nonconvex optimization, these convex sets and generalized concave functions are used in the book's second part, where decision-making and optimization problems under uncertainty are investigated. Uncertainty in the problem data often cannot be avoided when dealing with practical problems. Errors occur in real-world data for...

Development of a Support Tool for Complex Decision-Making in the Provision of Rural Maternity Care

Science.gov (United States)

Hearns, Glen; Klein, Michael C.; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea

2010-01-01

Context: Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. Objective: To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Design: Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Setting: Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Participants: Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). Results: We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Conclusions: Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the

Classification and optimization of training tools for NPP simulator

International Nuclear Information System (INIS)

Billoen, G. van

1994-01-01

The training cycle of nuclear power plant (NPP) operators has evolved during the last decade in parallel with the evolution of the training tools. The phases of the training cycle can be summarized as follows: (1) basic principle learning, (2) specific functional training, (3) full operating range training, and (4) detailed accident analyses. The progress in simulation technology and man/machine interface (MMI) gives the training centers new opportunities to improve their training methods and effectiveness in the transfer of knowledge. To take advantage of these new opportunities a significant investment in simulation tools may be required. It is therefore important to propose an optimized approach when dealing with the overall equipment program for these training centers. An overall look of tools proposed on the international simulation market shows that there is a need for systematic approach in this field. Classification of the different training tools needed for each training cycle is the basis for an optimized approach in terms of hardware configuration and software specifications of the equipment to install in training centers. The 'Multi-Function Simulator' is one of the approaches. (orig.) (3 tabs.)

Web-Based Tools for Data Visualization and Decision Support for South Asia

Science.gov (United States)

Jones, N.; Nelson, J.; Pulla, S. T.; Ames, D. P.; Souffront, M.; David, C. H.; Zaitchik, B. F.; Gatlin, P. N.; Matin, M. A.

2017-12-01

The objective of the NASA SERVIR project is to assist developing countries in using information provided by Earth observing satellites to assess and manage climate risks, land use, and water resources. We present a collection of web apps that integrate earth observations and in situ data to facilitate deployment of data and water resources models as decision-making tools in support of this effort. The interactive nature of web apps makes this an excellent medium for creating decision support tools that harness cutting edge modeling techniques. Thin client apps hosted in a cloud portal eliminates the need for the decision makers to procure and maintain the high performance hardware required by the models, deal with issues related to software installation and platform incompatibilities, or monitor and install software updates, a problem that is exacerbated for many of the regional SERVIR hubs where both financial and technical capacity may be limited. All that is needed to use the system is an Internet connection and a web browser. We take advantage of these technologies to develop tools which can be centrally maintained but openly accessible. Advanced mapping and visualization make results intuitive and information derived actionable. We also take advantage of the emerging standards for sharing water information across the web using the OGC and WMO approved WaterML standards. This makes our tools interoperable and extensible via application programming interfaces (APIs) so that tools and data from other projects can both consume and share the tools developed in our project. Our approach enables the integration of multiple types of data and models, thus facilitating collaboration between science teams in SERVIR. The apps developed thus far by our team process time-varying netCDF files from Earth observations and large-scale computer simulations and allow visualization and exploration via raster animation and extraction of time series at selected points and/or regions.

The Role of Heuristic Methods as a Decision-Making Tool in Aggregate Production Planning

OpenAIRE

Mahmood B. Ridha

2015-01-01

This study aims to explain the role of heuristic methods in the decision making process and as a tool for knowledge capture. As a result, we conclude that heuristic methods give better support to the decision maker than mathematical models in many cases especially when time and cost are critical factors in decision making.

An Architectural Decision Tool Based on Scenarios and Non-functional Requirements

OpenAIRE

Mr. Mahesh Parmar; Prof. W.U. Khan; Dr. Binod Kumar

2011-01-01

Software architecture design is often based on architects intuition and previous experience. Little methodological support is available, but there are still no effective solutions to guide the architectural design. The most difficult activity is the transformation from non-functional requirement specification into software architecture. To achieve above things proposed “An Architectural Decision Tool Based on Scenarios and Nonfunctional Requirementsâ€. In this proposed tool scenarios are fi...

Renovation versus New Construction and Building Decision Tool for Educational Facilities

OpenAIRE

Pope, Carrie; Marks, Eric; Back, Edward; Leopard, Tim; Love, Thomas

2016-01-01

Renovation of an existing building is an accomplished stem of the construction industry because it supplies financial diversification for construction stakeholders. Although several construction planning tools and stakeholder alignment exercises have been developed, no tool exists to assist project owners to decide between renovating an existing building and new construction with a comprehensive decision criteria. The objective of this research is to create and test a renovation versus new bu...

Optimization of sequential decisions by least squares Monte Carlo method

DEFF Research Database (Denmark)

Nishijima, Kazuyoshi; Anders, Annett

change adaptation measures, and evacuation of people and assets in the face of an emerging natural hazard event. Focusing on the last example, an efficient solution scheme is proposed by Anders and Nishijima (2011). The proposed solution scheme takes basis in the least squares Monte Carlo method, which...... is proposed by Longstaff and Schwartz (2001) for pricing of American options. The present paper formulates the decision problem in a more general manner and explains how the solution scheme proposed by Anders and Nishijima (2011) is implemented for the optimization of the formulated decision problem...

External Validation of a Decision Tool To Guide Post-Operative Management of Patients with Secondary Peritonitis.

Science.gov (United States)

Atema, Jasper J; Ram, Kim; Schultz, Marcus J; Boermeester, Marja A

Timely identification of patients in need of an intervention for abdominal sepsis after initial surgical management of secondary peritonitis is vital but complex. The aim of this study was to validate a decision tool for this purpose and to evaluate its potential to guide post-operative management. A prospective cohort study was conducted on consecutive adult patients undergoing surgery for secondary peritonitis in a single hospital. Assessments using the decision tool, based on one intra-operative and five post-operative variables, were performed on the second and third post-operative days and when the patients' clinical status deteriorated. Scores were compared with the clinical reference standard of persistent sepsis based on the clinical course or findings at imaging or surgery. Additionally, the potential of the decision tool to guide management in terms of diagnostic imaging in three previously defined score categories (low, intermediate, and high) was evaluated. A total of 161 assessments were performed in 69 patients. The majority of cases of secondary peritonitis (68%) were caused by perforation of the gastrointestinal tract. Post-operative persistent sepsis occurred in 28 patients. The discriminative capacity of the decision tool score was fair (area under the curve of the receiver operating characteristic = 0.79). The incidence rate differed significantly between the three score categories (p peritonitis, the decision tool score predicts with fair accuracy whether persistent sepsis is present.

Dutch gas distribution grid goes green: decision support tool for local biogas utilization

NARCIS (Netherlands)

Weidenaar, Teade; Hoekstra, Sipke; Wolters, Mannes

2011-01-01

A Decision Support Tool (DST) has been developed that will aid Distribution Service Operators (DSOs) in their decision making process on which investments to make in the gas distribution grid in order to facilitate the use of biogas. The DST considers both the conversion of biogas to electricity as

Open source Modeling and optimization tools for Planning

Energy Technology Data Exchange (ETDEWEB)

Peles, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-02-10

Open source modeling and optimization tools for planning The existing tools and software used for planning and analysis in California are either expensive, difficult to use, or not generally accessible to a large number of participants. These limitations restrict the availability of participants for larger scale energy and grid studies in the state. The proposed initiative would build upon federal and state investments in open source software, and create and improve open source tools for use in the state planning and analysis activities. Computational analysis and simulation frameworks in development at national labs and universities can be brought forward to complement existing tools. An open source platform would provide a path for novel techniques and strategies to be brought into the larger community and reviewed by a broad set of stakeholders.

Controller tuning with evolutionary multiobjective optimization a holistic multiobjective optimization design procedure

CERN Document Server

Reynoso Meza, Gilberto; Sanchis Saez, Javier; Herrero Durá, Juan Manuel

2017-01-01

This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO). It presents developments in tools, procedures and guidelines to facilitate this process, covering the three fundamental steps in the procedure: problem definition, optimization and decision-making. The book is divided into four parts. The first part, Fundamentals, focuses on the necessary theoretical background and provides specific tools for practitioners. The second part, Basics, examines a range of basic examples regarding the MOOD procedure for controller tuning, while the third part, Benchmarking, demonstrates how the MOOD procedure can be employed in several control engineering problems. The fourth part, Applications, is dedicated to implementing the MOOD procedure for controller tuning in real processes.

A simple tool to help decision making in infrastructure planning and ...

African Journals Online (AJOL)

2006-10-04

Oct 4, 2006 ... a tool to help decision making for planning and management of phytotreatment ... mental studies aimed at the quantitative estimation of biologi- cal processes .... water has been simulated with a logistic model assuming an.

Model based decision support for planning of road maintenance

NARCIS (Netherlands)

van Harten, Aart; Worm, J.M.; Worm, J.M.

1996-01-01

In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the

Cast Off expansion plan by rapid improvement through Optimization tool design, Tool Parameters and using Six Sigma’s ECRS Technique

Science.gov (United States)

Gopalakrishnan, T.; Saravanan, R.

2017-03-01

Powerful management concepts step-up the quality of the product, time saving in producing the product thereby increase the production rate, improves tools and techniques, work culture, work place and employee motivation and morale. In this paper discussed about the case study of optimizing the tool design, tool parameters to cast off expansion plan according ECRS technique. The proposed designs and optimal tool parameters yielded best results and meet the customer demand without expansion plan. Hence the work yielded huge savings of money (direct and indirect cost), time and improved the motivation and more of employees significantly.

Development of Decision-Making Automated System for Optimal Placement of Physical Access Control System’s Elements

Science.gov (United States)

Danilova, Olga; Semenova, Zinaida

2018-04-01

The objective of this study is a detailed analysis of physical protection systems development for information resources. The optimization theory and decision-making mathematical apparatus is used to formulate correctly and create an algorithm of selection procedure for security systems optimal configuration considering the location of the secured object’s access point and zones. The result of this study is a software implementation scheme of decision-making system for optimal placement of the physical access control system’s elements.

Selection of a tool to support decision making for site selection for high level waste - 15010

International Nuclear Information System (INIS)

Madeira, J.G.; Alvim, A.C.M.; Martins, V.B.; Monteiro, N.A.

2015-01-01

The aim of this paper is to create a panel comparing some of the key decision-making support tools used in situations with the characteristics of the problem of selecting suitable areas for constructing a final deep geologic repository. The tools presented in this work are also well-known and with easy implementation. The decision making process in issues of this kind is, in general, complex due to its multi-criteria nature and the conflicting opinions of various of stakeholders. Thus a comprehensive study was performed with the literature on this subject, specifically documents of the International Atomic Energy Agency - IAEA, regarding the importance of the criteria involved in the decision making process. Therefore, we highlighted 6 judgments attributes for selecting an adequate support tool: -) transparency and reliability, -) subjectivity, -) updating and adapting, -) multi-criteria analysis, -) ease of deployment, and -) application time. We have selected the following key decision-making support tools: AHP, Delphi, Brainstorm, Nominal Group Technique, and AHP-Delphi. Finally, the AHP-Delphi method has demonstrated to be more appropriate for managing the inherent multiple attributes to the problem proposed

Reward Rate Optimization in Two-Alternative Decision Making: Empirical Tests of Theoretical Predictions

Science.gov (United States)

Simen, Patrick; Contreras, David; Buck, Cara; Hu, Peter; Holmes, Philip; Cohen, Jonathan D.

2009-01-01

The drift-diffusion model (DDM) implements an optimal decision procedure for stationary, 2-alternative forced-choice tasks. The height of a decision threshold applied to accumulating information on each trial determines a speed-accuracy tradeoff (SAT) for the DDM, thereby accounting for a ubiquitous feature of human performance in speeded response…

Assessing Sustainability of Coral Reef Ecosystem Services using a Spatially-Explicit Decision Support Tool

Science.gov (United States)

Forecasting and communicating the potential outcomes of decision options requires support tools that aid in evaluating alternative scenarios in a user-friendly context and that highlight variables relevant to the decision options and valuable stakeholders. Envision is a GIS-base...

Do the right thing: the assumption of optimality in lay decision theory and causal judgment.

Science.gov (United States)

Johnson, Samuel G B; Rips, Lance J

2015-03-01

Human decision-making is often characterized as irrational and suboptimal. Here we ask whether people nonetheless assume optimal choices from other decision-makers: Are people intuitive classical economists? In seven experiments, we show that an agent's perceived optimality in choice affects attributions of responsibility and causation for the outcomes of their actions. We use this paradigm to examine several issues in lay decision theory, including how responsibility judgments depend on the efficacy of the agent's actual and counterfactual choices (Experiments 1-3), individual differences in responsibility assignment strategies (Experiment 4), and how people conceptualize decisions involving trade-offs among multiple goals (Experiments 5-6). We also find similar results using everyday decision problems (Experiment 7). Taken together, these experiments show that attributions of responsibility depend not only on what decision-makers do, but also on the quality of the options they choose not to take. Copyright © 2015 Elsevier Inc. All rights reserved.

Decision Support Model for Optimal Management of Coastal Gate

Science.gov (United States)

Ditthakit, Pakorn; Chittaladakorn, Suwatana

2010-05-01

The coastal areas are intensely settled by human beings owing to their fertility of natural resources. However, at present those areas are facing with water scarcity problems: inadequate water and poor water quality as a result of saltwater intrusion and inappropriate land-use management. To solve these problems, several measures have been exploited. The coastal gate construction is a structural measure widely performed in several countries. This manner requires the plan for suitably operating coastal gates. Coastal gate operation is a complicated task and usually concerns with the management of multiple purposes, which are generally conflicted one another. This paper delineates the methodology and used theories for developing decision support modeling for coastal gate operation scheduling. The developed model was based on coupling simulation and optimization model. The weighting optimization technique based on Differential Evolution (DE) was selected herein for solving multiple objective problems. The hydrodynamic and water quality models were repeatedly invoked during searching the optimal gate operations. In addition, two forecasting models:- Auto Regressive model (AR model) and Harmonic Analysis model (HA model) were applied for forecasting water levels and tide levels, respectively. To demonstrate the applicability of the developed model, it was applied to plan the operations for hypothetical system of Pak Phanang coastal gate system, located in Nakhon Si Thammarat province, southern part of Thailand. It was found that the proposed model could satisfyingly assist decision-makers for operating coastal gates under various environmental, ecological and hydraulic conditions.

A normative inference approach for optimal sample sizes in decisions from experience

Science.gov (United States)

Ostwald, Dirk; Starke, Ludger; Hertwig, Ralph

2015-01-01

“Decisions from experience” (DFE) refers to a body of work that emerged in research on behavioral decision making over the last decade. One of the major experimental paradigms employed to study experience-based choice is the “sampling paradigm,” which serves as a model of decision making under limited knowledge about the statistical structure of the world. In this paradigm respondents are presented with two payoff distributions, which, in contrast to standard approaches in behavioral economics, are specified not in terms of explicit outcome-probability information, but by the opportunity to sample outcomes from each distribution without economic consequences. Participants are encouraged to explore the distributions until they feel confident enough to decide from which they would prefer to draw from in a final trial involving real monetary payoffs. One commonly employed measure to characterize the behavior of participants in the sampling paradigm is the sample size, that is, the number of outcome draws which participants choose to obtain from each distribution prior to terminating sampling. A natural question that arises in this context concerns the “optimal” sample size, which could be used as a normative benchmark to evaluate human sampling behavior in DFE. In this theoretical study, we relate the DFE sampling paradigm to the classical statistical decision theoretic literature and, under a probabilistic inference assumption, evaluate optimal sample sizes for DFE. In our treatment we go beyond analytically established results by showing how the classical statistical decision theoretic framework can be used to derive optimal sample sizes under arbitrary, but numerically evaluable, constraints. Finally, we critically evaluate the value of deriving optimal sample sizes under this framework as testable predictions for the experimental study of sampling behavior in DFE. PMID:26441720

Research on optimization design of conformal cooling channels in hot stamping tool based on response surface methodology and multi-objective optimization

Directory of Open Access Journals (Sweden)

He Bin

2016-01-01

Full Text Available In order to optimize the layout of the conformal cooling channels in hot stamping tools, a response surface methodology and multi-objective optimization technique are proposed. By means of an Optimal Latin Hypercube experimental design method, a design matrix with 17 factors and 50 levels is generated. Three kinds of design variables, the radius Rad of the cooling channel, the distance H from the channel center to tool work surface and the ratio rat of each channel center, are optimized to determine the layout of cooling channels. The average temperature and temperature deviation of work surface are used to evaluate the cooling performance of hot stamping tools. On the basis of the experimental design results, quadratic response surface models are established to describe the relationship between the design variables and the evaluation objectives. The error analysis is performed to ensure the accuracy of response surface models. Then the layout of the conformal cooling channels is optimized in accordance with a multi-objective optimization method to find the Pareto optimal frontier which consists of some optimal combinations of design variables that can lead to an acceptable cooling performance.

Development and commissioning of decision support tools for sewerage management.

Science.gov (United States)

Manic, G; Printemps, C; Zug, M; Lemoine, C

2006-01-01

Managing sewerage systems is a highly complex task due to the dynamic nature of the facilities. Their performance strongly depends on the know-how applied by the operators. In order to define optimal operational settings, two decision support tools based on mathematical models have been developed. Moreover, easy-to-use interfaces have been created as well, aiding operators who presumably do not have the necessary skills to use modelling software. The two developed programs simulate the behaviour of both wastewater treatment plants (WWTP) and sewer network systems, respectively. They have essentially the same structure, including raw data management and statistical analysis, a simulation layer using the application programming interface of the applied software and a layer responsible for the representation of the obtained results. Four user modes are provided in the two software including the simulation of historical data using the applied and novel operational settings, as well as modes concerning prediction of possible operation periods and updates. Concerning the WWTP software, it was successfully installed in Nantes (France) in June 2004. Moreover, the one managing sewer networks has been deployed in Saint-Malo (France) in January 2005. This paper presents the structure of the developed software and the first results obtained during the commissioning phase.

Optimizing patient treatment decisions in an era of rapid technological advances: the case of hepatitis C treatment.

Science.gov (United States)

Liu, Shan; Brandeau, Margaret L; Goldhaber-Fiebert, Jeremy D

2017-03-01

How long should a patient with a treatable chronic disease wait for more effective treatments before accepting the best available treatment? We develop a framework to guide optimal treatment decisions for a deteriorating chronic disease when treatment technologies are improving over time. We formulate an optimal stopping problem using a discrete-time, finite-horizon Markov decision process. The goal is to maximize a patient's quality-adjusted life expectancy. We derive structural properties of the model and analytically solve a three-period treatment decision problem. We illustrate the model with the example of treatment for chronic hepatitis C virus (HCV). Chronic HCV affects 3-4 million Americans and has been historically difficult to treat, but increasingly effective treatments have been commercialized in the past few years. We show that the optimal treatment decision is more likely to be to accept currently available treatment-despite expectations for future treatment improvement-for patients who have high-risk history, who are older, or who have more comorbidities. Insights from this study can guide HCV treatment decisions for individual patients. More broadly, our model can guide treatment decisions for curable chronic diseases by finding the optimal treatment policy for individual patients in a heterogeneous population.

Humans Optimize Decision-Making by Delaying Decision Onset

Science.gov (United States)

Teichert, Tobias; Ferrera, Vincent P.; Grinband, Jack

2014-01-01

Why do humans make errors on seemingly trivial perceptual decisions? It has been shown that such errors occur in part because the decision process (evidence accumulation) is initiated before selective attention has isolated the relevant sensory information from salient distractors. Nevertheless, it is typically assumed that subjects increase accuracy by prolonging the decision process rather than delaying decision onset. To date it has not been tested whether humans can strategically delay decision onset to increase response accuracy. To address this question we measured the time course of selective attention in a motion interference task using a novel variant of the response signal paradigm. Based on these measurements we estimated time-dependent drift rate and showed that subjects should in principle be able trade speed for accuracy very effectively by delaying decision onset. Using the time-dependent estimate of drift rate we show that subjects indeed delay decision onset in addition to raising response threshold when asked to stress accuracy over speed in a free reaction version of the same motion-interference task. These findings show that decision onset is a critical aspect of the decision process that can be adjusted to effectively improve decision accuracy. PMID:24599295

An integrated knowledge-based and optimization tool for the sustainable selection of wastewater treatment process concepts

DEFF Research Database (Denmark)

Castillo, A.; Cheali, Peam; Gómez, V.

2016-01-01

The increasing demand on wastewater treatment plants (WWTPs) has involved an interest in improving the alternative treatment selection process. In this study, an integrated framework including an intelligent knowledge-based system and superstructure-based optimization has been developed and applied...... to a real case study. Hence, a multi-criteria analysis together with mathematical models is applied to generate a ranked short-list of feasible treatments for three different scenarios. Finally, the uncertainty analysis performed allows for increasing the quality and robustness of the decisions considering...... benefit and synergy is achieved when both tools are integrated because expert knowledge and expertise are considered together with mathematical models to select the most appropriate treatment alternative...

Decision Support System for Optimized Herbicide Dose in Spring Barley

DEFF Research Database (Denmark)

Sønderskov, Mette; Kudsk, Per; Mathiassen, Solvejg K

2014-01-01

Crop Protection Online (CPO) is a decision support system, which integrates decision algorithms quantifying the requirement for weed control and a herbicide dose model. CPO was designed to be used by advisors and farmers to optimize the choice of herbicide and dose. The recommendations from CPO...... as the Treatment Frequency Index (TFI)) compared to a high level of required weed control. The observations indicated that the current level of weed control required is robust for a range of weed scenarios. Weed plant numbers 3 wk after spraying indicated that the growth of the weed species were inhibited...

Contingency Contractor Optimization Phase 3 Sustainment Database Design Document - Contingency Contractor Optimization Tool - Prototype

Energy Technology Data Exchange (ETDEWEB)

Frazier, Christopher Rawls; Durfee, Justin David; Bandlow, Alisa; Gearhart, Jared Lee; Jones, Katherine A

2016-05-01

The Contingency Contractor Optimization Tool – Prototype (CCOT-P) database is used to store input and output data for the linear program model described in [1]. The database allows queries to retrieve this data and updating and inserting new input data.

Total Path Length and Number of Terminal Nodes for Decision Trees

KAUST Repository

Hussain, Shahid

2014-09-13

This paper presents a new tool for study of relationships between total path length (average depth) and number of terminal nodes for decision trees. These relationships are important from the point of view of optimization of decision trees. In this particular case of total path length and number of terminal nodes, the relationships between these two cost functions are closely related with space-time trade-off. In addition to algorithm to compute the relationships, the paper also presents results of experiments with datasets from UCI ML Repository1. These experiments show how two cost functions behave for a given decision table and the resulting plots show the Pareto frontier or Pareto set of optimal points. Furthermore, in some cases this Pareto frontier is a singleton showing the total optimality of decision trees for the given decision table.

Optimization of decision making to avoid stochastically predicted air traffic conflicts

Directory of Open Access Journals (Sweden)

В.М. Васильєв

2005-01-01

Full Text Available  The method of decision-making optimization on planning an aircraft trajectory to avoid potential conflict with restricted minimal level of separation standard is proposed. Evaluation and monitoring the conflict probability are made using the probabilistic composite method.

Decision Support Tool for Prioritization of Surveillance and Maintenance Investment

International Nuclear Information System (INIS)

Velez, L.Y.; Conley, T.B.

2009-01-01

The Department of Energy (DOE) currently faces a difficult task in the disposition of the numerous excess or to-be excessed facilities owned by the Department. Many of these facilities are in various physical conditions and contain potentially hazardous nuclear, chemical, radiological or industrial materials left behind as a byproduct of nuclear weapons production, nuclear powered naval vessels and commercial nuclear energy production. During the last period of a facility's life cycle, it is important that surveillance and maintenance (S and M) be adequate to maintain the facility within an appropriate safety envelope. Inadequate investment in maintenance can cause facilities to deteriorate to the point they are unsafe for human entry. Too often this can mean tremendous increases to cost during deactivation and decommissioning (D and D). However, experiences often show that once buildings have been declared excess and enter the transition phase (as defined in DOE G 430.1-5 Transition Implementation Guide), maintenance budgets are drastically reduced. This is justified by the desire to not spend money 'on a building that is being torn down'. The objective of this study was to provide the U.S. Department of Energy (DOE) Environmental Management (EM) federal project directors and their contractors with a decision support tool to aid in prioritizing S and M investment across a site's excess facilities so that the limited budget available can be used most effectively. The analytical hierarchy process (AHP), a multi-criteria decision making method developed by Dr. Thomas Saaty in the 1970's, was used to derive the weight of importance of a defined list of risk-based criteria and typical S and M activities. A total of 10 facilities at the Oak Ridge National Laboratory (ORNL) varying in perceived hazards and conditions were chosen to test the tool by evaluating them with respect to each risk criterion and combining these results with the weight of importance of the S and M

Decision and cost analysis of empirical antibiotic therapy of acute sinusitis in the era of increasing antimicrobial resistance: do we have an additional tool for antibiotic policy decisions?

Science.gov (United States)

Babela, Robert; Jarcuska, Pavol; Uraz, Vladimir; Krčméry, Vladimír; Jadud, Branislav; Stevlik, Jan; Gould, Ian M

2017-11-01

No previous analyses have attempted to determine optimal therapy for upper respiratory tract infections on the basis of cost-minimization models and the prevalence of antimicrobial resistance among respiratory pathogens in Slovakia. This investigation compares macrolides and cephalosporines for empirical therapy and look at this new tool from the aspect of potential antibiotic policy decision-making process. We employed a decision tree model to determine the threshold level of macrolides and cephalosporines resistance among community respiratory pathogens that would make cephalosporines or macrolides cost-minimising. To obtain information on clinical outcomes and cost of URTIs, a systematic review of the literature was performed. The cost-minimization model of upper respiratory tract infections (URTIs) treatment was derived from the review of literature and published models. We found that the mean cost of empirical treatment with macrolides for an URTIs was €93.27 when the percentage of resistant Streptococcus pneumoniae in the community was 0%; at 5%, the mean cost was €96.45; at 10%, €99.63; at 20%, €105.99, and at 30%, €112.36. Our model demonstrated that when the percentage of macrolide resistant Streptococcus pneumoniae exceeds 13.8%, use of empirical cephalosporines rather than macrolides minimizes the treatment cost of URTIs. Empirical macrolide therapy is less expensive than cephalosporines therapy for URTIs unless macrolide resistance exceeds 13.8% in the community. Results have important antibiotic policy implications, since presented model can be use as an additional decision-making tool for new guidelines and reimbursement processes by local authorities in the era of continual increase in antibiotic resistance.

Maintenance optimization after RCM

International Nuclear Information System (INIS)

Doyle, E.K.; Lee, C.-G.; Cho, D.

2005-01-01

Variant forms of RCM (Reliability Centered Maintenance) have been the maintenance optimizing tools of choice in industry for the last 20 years. Several such optimization techniques have been implemented at the Bruce Nuclear Station. Further cost refinement of the Station preventive maintenance strategy whereby decisions are based on statistical analysis of historical failure data are now being evaluated. The evaluation includes a requirement to demonstrate that earlier optimization projects have long term positive impacts. This proved to be a significant challenge. Eventually a methodology was developed using Crowe/AMSAA (Army Materials Systems Analysis Activity) plots to justify expenditures on further optimization efforts. (authors)

Lean production tools and decision latitude enable conditions for innovative learning in organizations: a multilevel analysis.

Science.gov (United States)

Fagerlind Ståhl, Anna-Carin; Gustavsson, Maria; Karlsson, Nadine; Johansson, Gun; Ekberg, Kerstin

2015-03-01

The effect of lean production on conditions for learning is debated. This study aimed to investigate how tools inspired by lean production (standardization, resource reduction, visual monitoring, housekeeping, value flow analysis) were associated with an innovative learning climate and with collective dispersion of ideas in organizations, and whether decision latitude contributed to these associations. A questionnaire was sent out to employees in public, private, production and service organizations (n = 4442). Multilevel linear regression analyses were used. Use of lean tools and decision latitude were positively associated with an innovative learning climate and collective dispersion of ideas. A low degree of decision latitude was a modifier in the association to collective dispersion of ideas. Lean tools can enable shared understanding and collective spreading of ideas, needed for the development of work processes, especially when decision latitude is low. Value flow analysis played a pivotal role in the associations. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Bayesian Networks as a Decision Tool for O&M of Offshore Wind Turbines

DEFF Research Database (Denmark)

Nielsen, Jannie Jessen; Sørensen, John Dalsgaard

2010-01-01

Costs to operation and maintenance (O&M) of offshore wind turbines are large. This paper presents how influence diagrams can be used to assist in rational decision making for O&M. An influence diagram is a graphical representation of a decision tree based on Bayesian Networks. Bayesian Networks...... offer efficient Bayesian updating of a damage model when imperfect information from inspections/monitoring is available. The extension to an influence diagram offers the calculation of expected utilities for decision alternatives, and can be used to find the optimal strategy among different alternatives...

Guide to Decision-Making Getting it more right than wrong

CERN Document Server

Drummond, Helga

2012-01-01

We make decisions, and these decisions make us and our organisations. And in theory, decision-making should be easy: a problem is identified, the decision-makers generate solutions, and choose the optimal one - and powerful mathematical tools are available to facilitate the task. Yet if it is all so simple why do organisations, both private and public sector, keep making mistakes - the results of which are borne by shareholders, employees, taxpayers and ultimately society at large? This guide to decision making. by leading decision science academic Helga Drummond, aims to improve decision-maki

[Decision making in the elderly: which tools for its evaluation by the clinician?].

Science.gov (United States)

Hommet, Caroline; Constans, Thierry; Atanasova, Boriana; Mondon, Karl

2010-09-01

Numerous decision-making situations occur in the activities of daily living. The consequences of the decision-making capacity disturbances may have a great impact on the patient's autonomy, financial management, and his or her reaction to a diagnosis as well as the ability to accept a therapeutic option or give informed consent. Decision-making is a complex and multi-dimensional process and brings into play attention, memory and executive functions, which are processed in the prefrontal cortex, particularly vulnerable in aging. A better comprehension of the mechanisms of decision-making, and of the resulting social consequences of their dysfunction may improve autonomy of the elderly. Unfortunately, we still lack appropriate tools to explore decision-making in routine practice.

Optimal Solutions of Multiproduct Batch Chemical Process Using Multiobjective Genetic Algorithm with Expert Decision System

Science.gov (United States)

Mokeddem, Diab; Khellaf, Abdelhafid

2009-01-01

Optimal design problem are widely known by their multiple performance measures that are often competing with each other. In this paper, an optimal multiproduct batch chemical plant design is presented. The design is firstly formulated as a multiobjective optimization problem, to be solved using the well suited non dominating sorting genetic algorithm (NSGA-II). The NSGA-II have capability to achieve fine tuning of variables in determining a set of non dominating solutions distributed along the Pareto front in a single run of the algorithm. The NSGA-II ability to identify a set of optimal solutions provides the decision-maker DM with a complete picture of the optimal solution space to gain better and appropriate choices. Then an outranking with PROMETHEE II helps the decision-maker to finalize the selection of a best compromise. The effectiveness of NSGA-II method with multiojective optimization problem is illustrated through two carefully referenced examples. PMID:19543537

Decision-Making for Supply Chain Integration Supply Chain Integration

CERN Document Server

Lettice, Fiona; Durowoju, Olatunde

2012-01-01

Effective supply chain integration, and the tight co-ordination it creates, is an essential pre-requisite for successful supply chain management.  Decision-Making for Supply Chain Integration is a practical reference on recent research in the area of supply chain integration focusing on distributed decision-making problems. Recent applications of various decision-making tools for integrating supply chains are covered including chapters focusing on: •Supplier selection, pricing strategy and inventory decisions in multi-level supply chains, •RFID-enabled distributed decision-making, •Operational risk issues and time-critical decision-making for sensitive logistics nodes, Modelling end to end processes to improve supply chain integration, and •Integrated systems to improve service delivery and optimize resource use. Decision-Making for Supply Chain Integration provides an insight into the tools and methodologies of this field with support from real-life case studies demonstrating successful application ...

OPTIMAL BUSINESS DECISION SYSTEM FOR MULTINATIONALS: A MULTIFACTOR ANALYSIS OF SELECTED MANUFACTURING FIRMS

Directory of Open Access Journals (Sweden)

Oforegbunam Thaddeus Ebiringa

2011-03-01

Full Text Available Traditional MIS has been made more effective through the integration of organization, human andtechnology factors into a decision matrix. The study is motivated by the need to find an optimal mixof interactive factors that will optimize the result of decision to apply ICT to manufacturingprocesses. The study used Factor analysis model based on the sampled opinion of forty (40operations/production managers and two thousand (2000 production line workers of three leadingmanufacturing firms: Uniliver Plc., PZ Plc, and Nigerian Breweries Plc operating in Aba IndustrialEstate of Nigeria. The results shows that a progressive mixed factor loading matrix, based on thepreferred ordered importance of resources factors in the formulation, implementation, monitoring,control and evaluation of ICT projects of the selected firms led to an average capability improvementof 0.764 in decision efficiency. This is considered strategic for achieving balanced corporate growthand development.

Informed public choices for low-carbon electricity portfolios using a computer decision tool.

Science.gov (United States)

Mayer, Lauren A Fleishman; Bruine de Bruin, Wändi; Morgan, M Granger

2014-04-01

Reducing CO2 emissions from the electricity sector will likely require policies that encourage the widespread deployment of a diverse mix of low-carbon electricity generation technologies. Public discourse informs such policies. To make informed decisions and to productively engage in public discourse, citizens need to understand the trade-offs between electricity technologies proposed for widespread deployment. Building on previous paper-and-pencil studies, we developed a computer tool that aimed to help nonexperts make informed decisions about the challenges faced in achieving a low-carbon energy future. We report on an initial usability study of this interactive computer tool. After providing participants with comparative and balanced information about 10 electricity technologies, we asked them to design a low-carbon electricity portfolio. Participants used the interactive computer tool, which constrained portfolio designs to be realistic and yield low CO2 emissions. As they changed their portfolios, the tool updated information about projected CO2 emissions, electricity costs, and specific environmental impacts. As in the previous paper-and-pencil studies, most participants designed diverse portfolios that included energy efficiency, nuclear, coal with carbon capture and sequestration, natural gas, and wind. Our results suggest that participants understood the tool and used it consistently. The tool may be downloaded from http://cedmcenter.org/tools-for-cedm/informing-the-public-about-low-carbon-technologies/ .

Analytical Tools to Improve Optimization Procedures for Lateral Flow Assays

Directory of Open Access Journals (Sweden)

Helen V. Hsieh

2017-05-01

Full Text Available Immunochromatographic or lateral flow assays (LFAs are inexpensive, easy to use, point-of-care medical diagnostic tests that are found in arenas ranging from a doctor’s office in Manhattan to a rural medical clinic in low resource settings. The simplicity in the LFA itself belies the complex task of optimization required to make the test sensitive, rapid and easy to use. Currently, the manufacturers develop LFAs by empirical optimization of material components (e.g., analytical membranes, conjugate pads and sample pads, biological reagents (e.g., antibodies, blocking reagents and buffers and the design of delivery geometry. In this paper, we will review conventional optimization and then focus on the latter and outline analytical tools, such as dynamic light scattering and optical biosensors, as well as methods, such as microfluidic flow design and mechanistic models. We are applying these tools to find non-obvious optima of lateral flow assays for improved sensitivity, specificity and manufacturing robustness.

GLIMPSE: A decision support tool for simultaneously achieving our air quality management and climate change mitigation goals

Science.gov (United States)

Pinder, R. W.; Akhtar, F.; Loughlin, D. H.; Henze, D. K.; Bowman, K. W.

2012-12-01

Poor air quality, ecosystem damages, and climate change all are caused by the combustion of fossil fuels, yet environmental management often addresses each of these challenges separately. This can lead to sub-optimal strategies and unintended consequences. Here we present GLIMPSE -- a decision support tool for simultaneously achieving our air quality and climate change mitigation goals. GLIMPSE comprises of two types of models, (i) the adjoint of the GEOS-Chem chemical transport model, to calculate the relationship between emissions and impacts at high spatial resolution, and (ii) the MARKAL energy system model, to calculate the relationship between energy technologies and emissions. This presentation will demonstrate how GLIMPSE can be used to explore energy scenarios to better achieve both improved air quality and mitigate climate change. Second, this presentation will discuss how space-based observations can be incorporated into GLIMPSE to improve decision-making. NASA satellite products, namely ozone radiative forcing from the Tropospheric Emission Spectrometer (TES), are used to extend GLIMPSE to include the impact of emissions on ozone radiative forcing. This provides a much needed observational constraint on ozone radiative forcing.

Ergodic optimization in the expanding case concepts, tools and applications

CERN Document Server

Garibaldi, Eduardo

2017-01-01

This book focuses on the interpretation of ergodic optimal problems as questions of variational dynamics, employing a comparable approach to that of the Aubry-Mather theory for Lagrangian systems. Ergodic optimization is primarily concerned with the study of optimizing probability measures. This work presents and discusses the fundamental concepts of the theory, including the use and relevance of Sub-actions as analogues to subsolutions of the Hamilton-Jacobi equation. Further, it provides evidence for the impressively broad applicability of the tools inspired by the weak KAM theory.

Application of a New Integrated Decision Support Tool (i-DST) for Urban Water Infrastructure: Analyzing Water Quality Compliance Pathways for Three Los Angeles Watersheds

Science.gov (United States)

Gallo, E. M.; Hogue, T. S.; Bell, C. D.; Spahr, K.; McCray, J. E.

2017-12-01

The water quality of receiving streams and waterbodies in urban watersheds are increasingly polluted from stormwater runoff. The implementation of Green Infrastructure (GI), which includes Low Impact Developments (LIDs) and Best Management Practices (BMPs), within a watershed aim to mitigate the effects of urbanization by reducing pollutant loads, runoff volume, and storm peak flow. Stormwater modeling is generally used to assess the impact of GIs implemented within a watershed. These modeling tools are useful for determining the optimal suite of GIs to maximize pollutant load reduction and minimize cost. However, stormwater management for most resource managers and communities also includes the implementation of grey and hybrid stormwater infrastructure. An integrated decision support tool, called i-DST, that allows for the optimization and comprehensive life-cycle cost assessment of grey, green, and hybrid stormwater infrastructure, is currently being developed. The i-DST tool will evaluate optimal stormwater runoff management by taking into account the diverse economic, environmental, and societal needs associated with watersheds across the United States. Three watersheds from southern California will act as a test site and assist in the development and initial application of the i-DST tool. The Ballona Creek, Dominguez Channel, and Los Angeles River Watersheds are located in highly urbanized Los Angeles County. The water quality of the river channels flowing through each are impaired by heavy metals, including copper, lead, and zinc. However, despite being adjacent to one another within the same county, modeling results, using EPA System for Urban Stormwater Treatment and Analysis INtegration (SUSTAIN), found that the optimal path to compliance in each watershed differs significantly. The differences include varied costs, suites of BMPs, and ancillary benefits. This research analyzes how the economic, physical, and hydrological differences between the three

Comparative Analysis of Investment Decision Models

Directory of Open Access Journals (Sweden)

Ieva Kekytė

2017-06-01

Full Text Available Rapid development of financial markets resulted new challenges for both investors and investment issues. This increased demand for innovative, modern investment and portfolio management decisions adequate for market conditions. Financial market receives special attention, creating new models, includes financial risk management and investment decision support systems.Researchers recognize the need to deal with financial problems using models consistent with the reality and based on sophisticated quantitative analysis technique. Thus, role mathematical modeling in finance becomes important. This article deals with various investments decision-making models, which include forecasting, optimization, stochatic processes, artificial intelligence, etc., and become useful tools for investment decisions.

Topology Optimization of an Actively Cooled Electronics Section for Downhole Tools

DEFF Research Database (Denmark)

Soprani, Stefano; Klaas Haertel, Jan Hendrik; Lazarov, Boyan Stefanov

2015-01-01

Active cooling systems represent a possible solution to the electronics overheating that occurs in wireline downhole tools operating in high temperature oil and gas wells. A Peltier cooler was chosen to maintain the downhole electronics to a tolerable temperature, but its integration into the dow......Active cooling systems represent a possible solution to the electronics overheating that occurs in wireline downhole tools operating in high temperature oil and gas wells. A Peltier cooler was chosen to maintain the downhole electronics to a tolerable temperature, but its integration......, according to the topology optimization results and assembly constraints, and compared to the optimized cases....

Contingency Contractor Optimization Phase 3 Sustainment Third-Party Software List - Contingency Contractor Optimization Tool - Prototype

Energy Technology Data Exchange (ETDEWEB)

Durfee, Justin David; Frazier, Christopher Rawls; Bandlow, Alisa

2016-05-01

The Contingency Contractor Optimization Tool - Prototype (CCOT-P) requires several third-party software packages. These are documented below for each of the CCOT-P elements: client, web server, database server, solver, web application and polling application.

Development of an integrated economic decision-support tool for the remediation of contaminated sites. Overview note

International Nuclear Information System (INIS)

Samson, R.; Bage, G.

2004-05-01

This report concludes the first design phase of an innovative software tool which, when completed, will allow managers of contaminated sites to make optimal decisions with respect to site remediation. The principal objective of the project was to develop the foundations for decision-support software (SITE VII) which will allow a comprehensive and rigorous approach to the comparison of remediation scenarios for sites contaminated with petroleum hydrocarbons. During this first phase of the project, the NSERC Industrial Chair in Site Remediation and Management of the Ecole Polytechnique de Montreal has completed four stages in the design of a decision-support tool that could be applied by any site manager using a simple computer. These four stages are: refinement of a technico-economic evaluation model; development of databases for five soil remediation technologies; design of a structure for integration of the databases with the technico-economic model; and simulation of the remediation of a contaminated site using the technico-economic model and a subset of the databases. In the interim report, the emphasis was placed on the development of the technico-economic model, supported by a very simple, single-technology simulation of remediation. In the present report, the priority is placed on the integration of the different components required for the creation of decision-support software based on the technico-economic model. An entire chapter of this report is devoted to elaborating the decision structure of the software. The treatment of information within the software is shown schematically and explained step-by-step. Five remediation technologies are handled by the software: three in-situ technologies (bio-venting, bio-slurping, bio-sparging) and two ex-situ technologies (thermal desorption, Bio-pile treatment). A technology file has been created for each technology, containing a brief description of the technology, its performance, its criteria of applicability

Updated Decision Support Tool for the Management of Waste and Debris from Radiological Incidents

International Nuclear Information System (INIS)

Lemieux, P.; Thorneloe, S.; Hayes, C.; Rodgers, M.; Christman, R.

2009-01-01

Unique challenges exist for the handling, transport, and disposal of debris resulting from homeland security incidents, disasters or other national emergencies. Access to guidance for facilitating decision making in the safe and timely disposal of debris is critical to helping restore a community or region and prevent further contamination or spread of disease. For a radiological dispersal device (RDD) or other radiological incident, proper characterization of the quantity, properties, and level of contamination of debris and decontamination residue can have a significant impact on cleanup costs and timelines. A suite of decision support tools (DSTs) is being developed by the U.S. EPA's Office of Research and Development to assist individuals responsible for making decisions associated with handling, transport, treatment, and disposal of such debris. The DSTs are location-specific to help identify specific facilities and contacts for making final disposal decisions. The DSTs provide quick reference to technical information, regulations, and other information to provide decision makers with assistance in guiding disposal decisions that are important for the protection of public health, first responders, and the environment. This tool is being developed in partnership with other U.S. government agencies, EPA program offices, industry, and state and local emergency response programs. (authors)

Collaboration and decision making tools for mobile groups

Science.gov (United States)

Abrahamyan, Suren; Balyan, Serob; Ter-Minasyan, Harutyun; Degtyarev, Alexander

2017-12-01

Nowadays the use of distributed collaboration tools is widespread in many areas of people activity. But lack of mobility and certain equipment-dependency creates difficulties and decelerates development and integration of such technologies. Also mobile technologies allow individuals to interact with each other without need of traditional office spaces and regardless of location. Hence, realization of special infrastructures on mobile platforms with help of ad-hoc wireless local networks could eliminate hardware-attachment and be useful also in terms of scientific approach. Solutions from basic internet-messengers to complex software for online collaboration equipment in large-scale workgroups are implementations of tools based on mobile infrastructures. Despite growth of mobile infrastructures, applied distributed solutions in group decisionmaking and e-collaboration are not common. In this article we propose software complex for real-time collaboration and decision-making based on mobile devices, describe its architecture and evaluate performance.

Developing GIS based decision-making tools in case of radiological contamination of agricultural soil

International Nuclear Information System (INIS)

Kepka, Pavel; Brom, Jakub; Prochazka, Jan; Vincikova, Hana; Pecharova, Emilie

2010-01-01

A set of supporting tools to help take remedial decisions in case of radiological contamination of agricultural produce is being developed within the EURANOS project. The tools are created in the ArcGIS environment in the Python programming language. So far, a simple model to estimate biomass in the contaminated area has been set up. This module will make it possible to estimate additional parameters, such as activity per kg or amount of waste created, which are useful when taking decision regarding premature crops harvesting. Areas where no remedial action is required can be also identified, of course

Decision support tools to support the operations of traffic management centers (TMC)

Science.gov (United States)

2011-01-31

The goal of this project is to develop decision support tools to support traffic management operations based on collected intelligent transportation system (ITS) data. The project developments are in accordance with the needs of traffic management ce...

A Web-Based Treatment Decision Support Tool for Patients With Advanced Knee Arthritis: Evaluation of User Interface and Content Design.

Science.gov (United States)

Zheng, Hua; Rosal, Milagros C; Li, Wenjun; Borg, Amy; Yang, Wenyun; Ayers, David C; Franklin, Patricia D

2018-04-30

Data-driven surgical decisions will ensure proper use and timing of surgical care. We developed a Web-based patient-centered treatment decision and assessment tool to guide treatment decisions among patients with advanced knee osteoarthritis who are considering total knee replacement surgery. The aim of this study was to examine user experience and acceptance of the Web-based treatment decision support tool among older adults. User-centered formative and summative evaluations were conducted for the tool. A sample of 28 patients who were considering total knee replacement participated in the study. Participants' responses to the user interface design, the clarity of information, as well as usefulness, satisfaction, and acceptance of the tool were collected through qualitative (ie, individual patient interviews) and quantitative (ie, standardized Computer System Usability Questionnaire) methods. Participants were older adults with a mean age of 63 (SD 11) years. Three-quarters of them had no technical questions using the tool. User interface design recommendations included larger fonts, bigger buttons, less colors, simpler navigation without extra "next page" click, less mouse movement, and clearer illustrations with simple graphs. Color-coded bar charts and outcome-specific graphs with positive action were easiest for them to understand the outcomes data. Questionnaire data revealed high satisfaction with the tool usefulness and interface quality, and also showed ease of use of the tool, regardless of age or educational status. We evaluated the usability of a patient-centered decision support tool designed for advanced knee arthritis patients to facilitate their knee osteoarthritis treatment decision making. The lessons learned can inform other decision support tools to improve interface and content design for older patients' use. ©Hua Zheng, Milagros C Rosal, Wenjun Li, Amy Borg, Wenyun Yang, David C Ayers, Patricia D Franklin. Originally published in JMIR Human

Considering Decision Variable Diversity in Multi-Objective Optimization: Application in Hydrologic Model Calibration

Science.gov (United States)

Sahraei, S.; Asadzadeh, M.

2017-12-01

Any modern multi-objective global optimization algorithm should be able to archive a well-distributed set of solutions. While the solution diversity in the objective space has been explored extensively in the literature, little attention has been given to the solution diversity in the decision space. Selection metrics such as the hypervolume contribution and crowding distance calculated in the objective space would guide the search toward solutions that are well-distributed across the objective space. In this study, the diversity of solutions in the decision-space is used as the main selection criteria beside the dominance check in multi-objective optimization. To this end, currently archived solutions are clustered in the decision space and the ones in less crowded clusters are given more chance to be selected for generating new solution. The proposed approach is first tested on benchmark mathematical test problems. Second, it is applied to a hydrologic model calibration problem with more than three objective functions. Results show that the chance of finding more sparse set of high-quality solutions increases, and therefore the analyst would receive a well-diverse set of options with maximum amount of information. Pareto Archived-Dynamically Dimensioned Search, which is an efficient and parsimonious multi-objective optimization algorithm for model calibration, is utilized in this study.

The Application of Time-Delay Dependent H∞ Control Model in Manufacturing Decision Optimization

Directory of Open Access Journals (Sweden)

Haifeng Guo

2015-01-01

Full Text Available This paper uses a time-delay dependent H∞ control model to analyze the effect of manufacturing decisions on the process of transmission from resources to capability. We establish a theoretical framework of manufacturing management process based on three terms: resource, manufacturing decision, and capability. Then we build a time-delay H∞ robust control model to analyze the robustness of manufacturing management. With the state feedback controller between manufacturing resources and decision, we find that there is an optimal decision to adjust the process of transmission from resources to capability under uncertain environment. Finally, we provide an example to prove the robustness of this model.

A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine

Science.gov (United States)

Bascetin, A.

2007-04-01

The selection of an optimal reclamation method is one of the most important factors in open-pit design and production planning. It also affects economic considerations in open-pit design as a function of plan location and depth. Furthermore, the selection is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by applying a systematic and logical approach to assess the priorities based on the inputs of several specialists from different functional areas within the mine company. The analytical hierarchy process (AHP) can be very useful in involving several decision makers with different conflicting objectives to arrive at a consensus decision. In this paper, the selection of an optimal reclamation method using an AHP-based model was evaluated for coal production in an open-pit coal mine located at Seyitomer region in Turkey. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a reclamation method that satisfies optimal specifications. Also, it is found that the decision process is systematic and using the proposed model can reduce the time taken to select a optimal method.

Alternative Fuel Transportation Optimization Tool : Description, Methodology, and Demonstration Scenarios.

Science.gov (United States)

2015-09-01

This report describes an Alternative Fuel Transportation Optimization Tool (AFTOT), developed by the U.S. Department of Transportation (DOT) Volpe National Transportation Systems Center (Volpe) in support of the Federal Aviation Administration (FAA)....

"Best Case/Worst Case": Qualitative Evaluation of a Novel Communication Tool for Difficult in-the-Moment Surgical Decisions.

Science.gov (United States)

Kruser, Jacqueline M; Nabozny, Michael J; Steffens, Nicole M; Brasel, Karen J; Campbell, Toby C; Gaines, Martha E; Schwarze, Margaret L

2015-09-01

To evaluate a communication tool called "Best Case/Worst Case" (BC/WC) based on an established conceptual model of shared decision-making. Focus group study. Older adults (four focus groups) and surgeons (two focus groups) using modified questions from the Decision Aid Acceptability Scale and the Decisional Conflict Scale to evaluate and revise the communication tool. Individuals aged 60 and older recruited from senior centers (n = 37) and surgeons from academic and private practices in Wisconsin (n = 17). Qualitative content analysis was used to explore themes and concepts that focus group respondents identified. Seniors and surgeons praised the tool for the unambiguous illustration of multiple treatment options and the clarity gained from presentation of an array of treatment outcomes. Participants noted that the tool provides an opportunity for in-the-moment, preference-based deliberation about options and a platform for further discussion with other clinicians and loved ones. Older adults worried that the format of the tool was not universally accessible for people with different educational backgrounds, and surgeons had concerns that the tool was vulnerable to physicians' subjective biases. The BC/WC tool is a novel decision support intervention that may help facilitate difficult decision-making for older adults and their physicians when considering invasive, acute medical treatments such as surgery. © 2015, Copyright the Authors Journal compilation © 2015, The American Geriatrics Society.

Psychiatric service staff perceptions of implementing a shared decision-making tool: a process evaluation study.

Science.gov (United States)

Schön, Ulla-Karin; Grim, Katarina; Wallin, Lars; Rosenberg, David; Svedberg, Petra

2018-12-01

Shared decision making, SDM, in psychiatric services, supports users to experience a greater sense of involvement in treatment, self-efficacy, autonomy and reduced coercion. Decision tools adapted to the needs of users have the potential to support SDM and restructure how users and staff work together to arrive at shared decisions. The aim of this study was to describe and analyse the implementation process of an SDM intervention for users of psychiatric services in Sweden. The implementation was studied through a process evaluation utilizing both quantitative and qualitative methods. In designing the process evaluation for the intervention, three evaluation components were emphasized: contextual factors, implementation issues and mechanisms of impact. The study addresses critical implementation issues related to decision-making authority, the perceived decision-making ability of users and the readiness of the service to increase influence and participation. It also emphasizes the importance of facilitation, as well as suggesting contextual adaptations that may be relevant for the local organizations. The results indicate that staff perceived the decision support tool as user-friendly and useful in supporting participation in decision-making, and suggest that such concrete supports to participation can be a factor in implementation if adequate attention is paid to organizational contexts and structures.

Decision Making with Imperfect Decision Makers

CERN Document Server

Guy, Tatiana Valentine; Wolpert, David H

2012-01-01

Prescriptive Bayesian decision making has reached a high level of maturity and is well-supported algorithmically. However, experimental data shows that real decision makers choose such Bayes-optimal decisions surprisingly infrequently, often making decisions that are badly sub-optimal. So prevalent is such imperfect decision-making that it should be accepted as an inherent feature of real decision makers living within interacting societies. To date such societies have been investigated from an economic and gametheoretic perspective, and even to a degree from a physics perspective. However, lit

A methodological model to assist in the optimization and risk management of mining investment decisions

International Nuclear Information System (INIS)

Botin, Jose A; Guzman, Ronald R; Smith, Martin L

2011-01-01

Identifying, quantifying, and minimizing technical risks associated with investment decisions is a key challenge for mineral industry decision makers and investors. However, risk analysis in most bankable mine feasibility studies are based on the stochastic modeling of project N et Present Value (NPV)which, in most cases, fails to provide decision makers with a truly comprehensive analysis of risks associated with technical and management uncertainty and, as a result, are of little use for risk management and project optimization. This paper presents a value-chain risk management approach where project risk is evaluated for each step of the project life cycle, from exploration to mine closure, and risk management is performed as a part of a stepwise value-added optimization process.

Rational risk-based decision support for drinking water well managers by optimized monitoring designs

Science.gov (United States)

Enzenhöfer, R.; Geiges, A.; Nowak, W.

2011-12-01

Advection-based well-head protection zones are commonly used to manage the contamination risk of drinking water wells. Considering the insufficient knowledge about hazards and transport properties within the catchment, current Water Safety Plans recommend that catchment managers and stakeholders know, control and monitor all possible hazards within the catchments and perform rational risk-based decisions. Our goal is to supply catchment managers with the required probabilistic risk information, and to generate tools that allow for optimal and rational allocation of resources between improved monitoring versus extended safety margins and risk mitigation measures. To support risk managers with the indispensable information, we address the epistemic uncertainty of advective-dispersive solute transport and well vulnerability (Enzenhoefer et al., 2011) within a stochastic simulation framework. Our framework can separate between uncertainty of contaminant location and actual dilution of peak concentrations by resolving heterogeneity with high-resolution Monte-Carlo simulation. To keep computational costs low, we solve the reverse temporal moment transport equation. Only in post-processing, we recover the time-dependent solute breakthrough curves and the deduced well vulnerability criteria from temporal moments by non-linear optimization. Our first step towards optimal risk management is optimal positioning of sampling locations and optimal choice of data types to reduce best the epistemic prediction uncertainty for well-head delineation, using the cross-bred Likelihood Uncertainty Estimator (CLUE, Leube et al., 2011) for optimal sampling design. Better monitoring leads to more reliable and realistic protection zones and thus helps catchment managers to better justify smaller, yet conservative safety margins. In order to allow an optimal choice in sampling strategies, we compare the trade-off in monitoring versus the delineation costs by accounting for ill

Development and application of a living probabilistic safety assessment tool: Multi-objective multi-dimensional optimization of surveillance requirements in NPPs considering their ageing

International Nuclear Information System (INIS)

Kančev, Duško; Čepin, Marko; Gjorgiev, Blaže

2014-01-01

. Substantial risk reduction, supplemented with reduction in costs and dose is implicated if the selected existing surveillance test intervals are replaced with the corresponding optimal ones. By this, the benefits of applying risk-informed decision making are once more emphasized. Also, the importance of the inclusion of safety equipment ageing in the plant long-term probabilistic safety assessment is recognized. - Highlights: • New model for assessing time-dependent component unavailability in NPP is developed. • Component ageing is considered within the model. • The model is coupled to PSA software used for system and plant level modelling. • Living PSA tool for time-dependent risk analysis on plant level is developed. • Plant level multi-objective optimization of surveillance requirements is performed

Evaluation of the need for stochastic optimization of out-of-core nuclear fuel management decisions

International Nuclear Information System (INIS)

Thomas, R.L. Jr.

1989-01-01

Work has been completed on utilizing mathematical optimization techniques to optimize out-of-core nuclear fuel management decisions. The objective of such optimization is to minimize the levelized fuel cycle cost over some planning horizon. Typical decision variables include feed enrichments and number of assemblies, burnable poison requirements, and burned fuel to reinsert for every cycle in the planning horizon. Engineering constraints imposed consist of such items as discharge burnup limits, maximum enrichment limit, and target cycle energy productions. Earlier the authors reported on the development of the OCEON code, which employs the integer Monte Carlo Programming method as the mathematical optimization method. The discharge burnpups, and feed enrichment and burnable poison requirements are evaluated, initially employing a linear reactivity core physics model and refined using a coarse mesh nodal model. The economic evaluation is completed using a modification of the CINCAS methodology. Interest now is to assess the need for stochastic optimization, which will account for cost components and cycle energy production uncertainties. The implication of the present studies is that stochastic optimization in regard to cost component uncertainties need not be completed since deterministic optimization will identify nearly the same family of near-optimum cycling schemes

CORAL off-line: an object-oriented tool for optimal control of sewer networks

OpenAIRE

Figueras, J.; Cembrano, Gabriela; Puig, Vicenç; Quevedo, Joseba; Salamero Sansalvado, María; Marti Marques, Joaquim

2002-01-01

This paper describes a tool to aid in the analysis and design of combined sewer networks. Complex drainage systems include actuators, like flow-diversion gates and detention tanks, which should be optimally controlled in order to minimize flooding and combined sewer overflow (CSO). Through these optimisations volume to waste water treatment plants (WWTP) is maximised. CORAL is a tool able to model a combined sewer network, simulate rain events, calculate actuators optimal policies, reproduce ...

Decision support systems for recovery of endangered species

International Nuclear Information System (INIS)

Armstrong, C.E.

1995-01-01

The listing of a species as endangered under the Endangered Species Act invokes a suite of responses to help improve conditions for the recovery of that species, to include identification of stressors contributing to population loss, decision analysis of the impacts of proposed recovery options, and implementation of optimal recovery measures. The ability of a decision support system to quantify inherent stressor uncertainties and to identify the key stressors that can be controlled or eliminated becomes key to ensuring the recovery of an endangered species. The listing of the Snake River sockeye, spring/summer chinook, and fall chinook salmon species in the Snake River as endangered provides a vivid example of the importance of sophisticated decision support systems. Operational and physical changes under consideration at eight of the hydroelectric dams along the Columbia and Lower Snake River pose significant financial impacts to a variety of stakeholders involved in the salmon population recovery process and carry significant uncertainties of outcome. A decision support system is presented to assist in the identification of optimal recovery actions for this example that includes the following: creation of datamarts of information on environmental, engineering, and ecological values that influence species survival; incorporation of decision analysis tools to determine optimal decision policies; and the use of geographic information systems (GIS) to provide a context for decision analysis and to communicate the impacts of decision policies

A web-based neurological pain classifier tool utilizing Bayesian decision theory for pain classification in spinal cord injury patients

Science.gov (United States)

Verma, Sneha K.; Chun, Sophia; Liu, Brent J.

2014-03-01

Pain is a common complication after spinal cord injury with prevalence estimates ranging 77% to 81%, which highly affects a patient's lifestyle and well-being. In the current clinical setting paper-based forms are used to classify pain correctly, however, the accuracy of diagnoses and optimal management of pain largely depend on the expert reviewer, which in many cases is not possible because of very few experts in this field. The need for a clinical decision support system that can be used by expert and non-expert clinicians has been cited in literature, but such a system has not been developed. We have designed and developed a stand-alone tool for correctly classifying pain type in spinal cord injury (SCI) patients, using Bayesian decision theory. Various machine learning simulation methods are used to verify the algorithm using a pilot study data set, which consists of 48 patients data set. The data set consists of the paper-based forms, collected at Long Beach VA clinic with pain classification done by expert in the field. Using the WEKA as the machine learning tool we have tested on the 48 patient dataset that the hypothesis that attributes collected on the forms and the pain location marked by patients have very significant impact on the pain type classification. This tool will be integrated with an imaging informatics system to support a clinical study that will test the effectiveness of using Proton Beam radiotherapy for treating spinal cord injury (SCI) related neuropathic pain as an alternative to invasive surgical lesioning.

A Fuzzy Max–Min Decision Bi-Level Fuzzy Programming Model for Water Resources Optimization Allocation under Uncertainty

Directory of Open Access Journals (Sweden)

Chongfeng Ren

2018-04-01

Full Text Available Water competing conflict among water competing sectors from different levels should be taken under consideration during the optimization allocation of water resources. Furthermore, uncertainties are inevitable in the optimization allocation of water resources. In order to deal with the above problems, this study developed a fuzzy max–min decision bi-level fuzzy programming model. The developed model was then applied to a case study in Wuwei, Gansu Province, China. In this study, the net benefit and yield were regarded as the upper-level and lower-level objectives, respectively. Optimal water resource plans were obtained under different possibility levels of fuzzy parameters, which could deal with water competing conflict between the upper level and the lower level effectively. The obtained results are expected to make great contribution in helping local decision-makers to make decisions on dealing with the water competing conflict between the upper and lower level and the optimal use of water resources under uncertainty.

Evaluation of a clinical decision support tool for osteoporosis disease management: protocol for an interrupted time series design.

Science.gov (United States)

Kastner, Monika; Sawka, Anna; Thorpe, Kevin; Chignel, Mark; Marquez, Christine; Newton, David; Straus, Sharon E

2011-07-22

Osteoporosis affects over 200 million people worldwide at a high cost to healthcare systems. Although guidelines on assessing and managing osteoporosis are available, many patients are not receiving appropriate diagnostic testing or treatment. Findings from a systematic review of osteoporosis interventions, a series of mixed-methods studies, and advice from experts in osteoporosis and human-factors engineering were used collectively to develop a multicomponent tool (targeted to family physicians and patients at risk for osteoporosis) that may support clinical decision making in osteoporosis disease management at the point of care. A three-phased approach will be used to evaluate the osteoporosis tool. In phase 1, the tool will be implemented in three family practices. It will involve ensuring optimal functioning of the tool while minimizing disruption to usual practice. In phase 2, the tool will be pilot tested in a quasi-experimental interrupted time series (ITS) design to determine if it can improve osteoporosis disease management at the point of care. Phase 3 will involve conducting a qualitative postintervention follow-up study to better understand participants' experiences and perceived utility of the tool and readiness to adopt the tool at the point of care. The osteoporosis tool has the potential to make several contributions to the development and evaluation of complex, chronic disease interventions, such as the inclusion of an implementation strategy prior to conducting an evaluation study. Anticipated benefits of the tool may be to increase awareness for patients about osteoporosis and its associated risks and provide an opportunity to discuss a management plan with their physician, which may all facilitate patient self-management.

Critical review of decision support tools for sustainability assessment of site remediation options.

Science.gov (United States)

Huysegoms, Lies; Cappuyns, Valérie

2017-07-01

In Europe alone, there are more than 2,5 million potentially contaminated sites of which 14% are expected to require remediation. Contaminated soil and groundwater can cause damage to human health as well as to valuable ecosystems. Globally more attention has been paid to this problem of soil contamination in the past decades. For example, more than 58 000 sites have been remediated in Europe between 2006 and 2011. Together with this increase in remediation projects there has been a surge in the development of new remediation technologies and decision support tools to be able to match every site and its specific characteristics to the best possible remediation alternative. In the past years the development of decision support tools (DST) has evolved in a more sustainable direction. Several DSTs added the claim not only to denote effective or technologically and economically feasible remediation alternatives but also to point out the more or most sustainable remediation alternatives. These trends in the evaluation of site remediation options left users with a confusing clew of possibly applicable tools to assist them in decision making for contaminated site remediation. This review provides a structured overview on the extent decision support tools for contaminated site remediation, that claim to assist in choosing the most sustainable remediation alternative, actually include the different elements of sustainability proposed in our assessment framework. The review contains an in-depth analysis of thirteen tools specifically developed to assess the sustainability of site remediation alternatives. This analysis is based on six criteria derived from the definition of sustainable development of the Brundtland report. The six criteria were concretized by using the three pillars of sustainability, applied to site remediation according to the SuRF-UK framework, two criteria derived from Life Cycle Assessment and Cost-Benefit Analysis, and an 'User friendly' criterion

Semi-automatic tool to ease the creation and optimization of GPU programs

DEFF Research Database (Denmark)

Jepsen, Jacob

2014-01-01

We present a tool that reduces the development time of GPU-executable code. We implement a catalogue of common optimizations specific to the GPU architecture. Through the tool, the programmer can semi-automatically transform a computationally-intensive code section into GPU-executable form...... of the transformations can be performed automatically, which makes the tool usable for both novices and experts in GPU programming....

Methods and tools for analysis and optimization of power plants

Energy Technology Data Exchange (ETDEWEB)

Assadi, Mohsen

2000-09-01

The most noticeable advantage of the introduction of the computer-aided tools in the field of power generation, has been the ability to study the plant's performance prior to the construction phase. The results of these studies have made it possible to change and adjust the plant layout to match the pre-defined requirements. Further development of computers in recent years has opened up for implementation of new features in the existing tools and also for the development of new tools for specific applications, like thermodynamic and economic optimization, prediction of the remaining component life time, and fault diagnostics, resulting in improvement of the plant's performance, availability and reliability. The most common tools for pre-design studies are heat and mass balance programs. Further thermodynamic and economic optimization of plant layouts, generated by the heat and mass balance programs, can be accomplished by using pinch programs, exergy analysis and thermoeconomics. Surveillance and fault diagnostics of existing systems can be performed by using tools like condition monitoring systems and artificial neural networks. The increased number of tools and their various construction and application areas make the choice of the most adequate tool for a certain application difficult. In this thesis the development of different categories of tools and techniques, and their application area are reviewed and presented. Case studies on both existing and theoretical power plant layouts have been performed using different commercially available tools to illuminate their advantages and shortcomings. The development of power plant technology and the requirements for new tools and measurement systems have been briefly reviewed. This thesis contains also programming techniques and calculation methods concerning part-load calculations using local linearization, which has been implemented in an inhouse heat and mass balance program developed by the author

Intensity-modulated radiation therapy (IMRT) for locally advanced paranasal sinus tumors: incorporating clinical decisions in the optimization process

International Nuclear Information System (INIS)

Tsien, Christina; Eisbruch, Avraham; McShan, Daniel; Kessler, Marc; Marsh, Robin C.; Fraass, Benedick

2003-01-01

, tradeoff values between OP toxicity and PTV coverage can be compared for different clinical decisions. The information derived can then be used to individualize the parameters within the optimization system. This process of determining clinical tradeoffs associated with different clinical decisions may be a useful tool in other sites

Defining criteria related to wastes for use in multi-criteria decision tool for nuclear accidents

Energy Technology Data Exchange (ETDEWEB)

Silva, Diogo N.G.; Guimaraes, Jean R.D., E-mail: dneves@biof.ufrj.br, E-mail: jeanrdg@biof.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Instituto de Biofisica Carlos Chagas Filho; Rochedo, Elaine R.R.; De Luca, Christiano, E-mail: elainerochedo@gmail.com, E-mail: christiano_luca@hotmail.com [Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear; Rochedo, Pedro R.R., E-mail: rochedopedro@gmail.com [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Instituto Alberto Luiz Coimbra de Pos-Graduacao e Pesquisa de Engenharia

2013-07-01

The selection of protective measures and strategies for remediation of contaminated areas after a nuclear accident must be based on previously established criteria in order to prevent stress of the population and the unnecessary exposure of workers. After a nuclear accident resulting in environmental contamination, decisions on remediation of areas is complex due to the large numbers of factors involved in decontamination processes. This work is part of a project which aims to develop a multi-criteria tool to support a decision-making process in cases of a radiological or a nuclear accident in Brazil. First, a database of remediation strategies for contaminated areas was created. In this process, the most relevant aspects for the implementation of these strategies were considered, including technical criteria regarding aspects related to the generation of wastes in a reference urban area, which are discussed in this paper. The specific objective of this study is to define criteria for the aspects of radioactive wastes, resulted by the implementation of some urban measures, in order to be incorporated in a multi-criteria decision tool. Main aspects considered were the type, the amount and the type of treatment necessary for each procedure. The decontamination procedures are then classified according to the selected criteria in order to feed the multi-criteria decision tool. This paper describes the steps for the establishment of these criteria and evaluates the potential for future applications in order to improve predictions and to support the decisions to be made. (author)

Defining criteria related to wastes for use in multi-criteria decision tool for nuclear accidents

International Nuclear Information System (INIS)

Silva, Diogo N.G.; Guimaraes, Jean R.D.; Rochedo, Elaine R.R.; De Luca, Christiano; Rochedo, Pedro R.R.

2013-01-01

The selection of protective measures and strategies for remediation of contaminated areas after a nuclear accident must be based on previously established criteria in order to prevent stress of the population and the unnecessary exposure of workers. After a nuclear accident resulting in environmental contamination, decisions on remediation of areas is complex due to the large numbers of factors involved in decontamination processes. This work is part of a project which aims to develop a multi-criteria tool to support a decision-making process in cases of a radiological or a nuclear accident in Brazil. First, a database of remediation strategies for contaminated areas was created. In this process, the most relevant aspects for the implementation of these strategies were considered, including technical criteria regarding aspects related to the generation of wastes in a reference urban area, which are discussed in this paper. The specific objective of this study is to define criteria for the aspects of radioactive wastes, resulted by the implementation of some urban measures, in order to be incorporated in a multi-criteria decision tool. Main aspects considered were the type, the amount and the type of treatment necessary for each procedure. The decontamination procedures are then classified according to the selected criteria in order to feed the multi-criteria decision tool. This paper describes the steps for the establishment of these criteria and evaluates the potential for future applications in order to improve predictions and to support the decisions to be made. (author)

Mapping data through concept maps: an auxiliary tool for decision making regarding institutional projects

International Nuclear Information System (INIS)

D’Avila, Adriana L.

2017-01-01

This paper reports a data mapping construction aimed to subsidize the decision making process regarding institutional projects, at different levels of responsibility, at the Instituto de Engenharia Nuclear. The conception models a systemic and adaptive tool which is based on the concept mapping theory developed by Novak. The Instituto de Engenharia Nuclear (IEN) is a research center of the Comissão de Energia Nuclear (CNEN), an autarchy attached to Ministério da Ciência, Tecnologia, Inovações e Comunicações. The main focus of IEN is research and development of nuclear science and technology. The developed tool creates a more effective and accessible way of sharing information. However, beyond project data integration into a specific instrument, it also has the intent to compensate the consequences of the continued reduction of the number of workers at IEN over recent years. The recent CNEN management report, published in 2016, showed the problematic situation caused by the loss of workers, stressing the high number of pensions granted and to be granted in the near future. The loss of labor force, besides exposing the urgent need for optimizing knowledge management efforts, also sheds light into another problem: the need for grouping responsibilities among the remaining workers. In this respect, the tool developed helps to face this challenge, enhancing autonomy at different levels but preserving the institutional guidelines. To conclude the report, and in order to exemplify the method, the paper also describes the map construction relative an innovative project proposal in a joint development towards the nuclear area. (author)

Mapping data through concept maps: an auxiliary tool for decision making regarding institutional projects

Energy Technology Data Exchange (ETDEWEB)

D’Avila, Adriana L., E-mail: adriana@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil). Divisão de Engenharia Nuclear

2017-11-01

This paper reports a data mapping construction aimed to subsidize the decision making process regarding institutional projects, at different levels of responsibility, at the Instituto de Engenharia Nuclear. The conception models a systemic and adaptive tool which is based on the concept mapping theory developed by Novak. The Instituto de Engenharia Nuclear (IEN) is a research center of the Comissão de Energia Nuclear (CNEN), an autarchy attached to Ministério da Ciência, Tecnologia, Inovações e Comunicações. The main focus of IEN is research and development of nuclear science and technology. The developed tool creates a more effective and accessible way of sharing information. However, beyond project data integration into a specific instrument, it also has the intent to compensate the consequences of the continued reduction of the number of workers at IEN over recent years. The recent CNEN management report, published in 2016, showed the problematic situation caused by the loss of workers, stressing the high number of pensions granted and to be granted in the near future. The loss of labor force, besides exposing the urgent need for optimizing knowledge management efforts, also sheds light into another problem: the need for grouping responsibilities among the remaining workers. In this respect, the tool developed helps to face this challenge, enhancing autonomy at different levels but preserving the institutional guidelines. To conclude the report, and in order to exemplify the method, the paper also describes the map construction relative an innovative project proposal in a joint development towards the nuclear area. (author)

Five-axis Control Processing Using NC Machine Tools : A Tool Posture Decision Using the Tangent Slope at a Cut Point on a Work

OpenAIRE

小島, 龍広; 西田, 知照; 扇谷, 保彦

2003-01-01

This report deals with the way to decide tool posture and the way to analytically calculate tool path for the work shape requiring 5-axis control machining. In the tool path calculation, basic equations are derived using the principle that the tangent slope at a cut point on a work and the one at a cutting point on a tool edge are identical. A tool posture decision procedure using the tangent slope at each cut point on a work is proposed for any shape of tool edge. The valid- ity of the way t...

Parameter identification and optimization of slide guide joint of CNC machine tools

Science.gov (United States)

Zhou, S.; Sun, B. B.

2017-11-01

The joint surface has an important influence on the performance of CNC machine tools. In order to identify the dynamic parameters of slide guide joint, the parametric finite element model of the joint is established and optimum design method is used based on the finite element simulation and modal test. Then the mode that has the most influence on the dynamics of slip joint is found through harmonic response analysis. Take the frequency of this mode as objective, the sensitivity analysis of the stiffness of each joint surface is carried out using Latin Hypercube Sampling and Monte Carlo Simulation. The result shows that the vertical stiffness of slip joint surface constituted by the bed and the slide plate has the most obvious influence on the structure. Therefore, this stiffness is taken as the optimization variable and the optimal value is obtained through studying the relationship between structural dynamic performance and stiffness. Take the stiffness values before and after optimization into the FEM of machine tool, and it is found that the dynamic performance of the machine tool is improved.

Nonsmooth Optimization Algorithms, System Theory, and Software Tools

Science.gov (United States)

1993-04-13

Optimization Algorithms, System Theory , and Scftware Tools" AFOSR-90-OO68 L AUTHOR($) Elijah Polak -Professor and Principal Investigator 7. PERFORMING...NSN 754Q-01-2W0-S500 Standard Form 295 (69O104 Draft) F’wsa*W by hA Sit 230.1""V AFOSR-90-0068 NONSMO0 TH OPTIMIZA TION A L GORI THMS, SYSTEM THEORY , AND

No perfect tools: trade-offs of sustainability principles and user requirements in designing support tools for land-use decisions between greenfields and brownfields.

Science.gov (United States)

Bartke, Stephan; Schwarze, Reimund

2015-04-15

The EU Soil Thematic Strategy calls for the application of sustainability concepts and methods as part of an integrated policy to prevent soil degradation and to increase the re-use of brownfields. Although certain general principles have been proposed for the evaluation of sustainable development, the practical application of sustainability assessment tools (SATs) is contingent on the actual requirements of tool users, e.g. planners or investors, to pick up such instruments in actual decision making. We examine the normative sustainability principles that need to be taken into account in order to make sound land-use decisions between new development on greenfield sites and the regeneration of brownfields - and relate these principles to empirically observed user requirements and the properties of available SATs. In this way we provide an overview of approaches to sustainability assessment. Three stylized approaches, represented in each case by a typical tool selected from the literature, are presented and contrasted with (1) the norm-oriented Bellagio sustainability principles and (2) the requirements of three different stakeholder groups: decision makers, scientists/experts and representatives of the general public. The paper disentangles some of the inevitable trade-offs involved in seeking to implement sustainable land-use planning, i.e. between norm orientation and holism, broad participation and effective communication. It concludes with the controversial assessment that there are no perfect tools and that to be meaningful the user requirements of decision makers must take precedence over those of other interest groups in the design of SATs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimization Tool for Direct Water Cooling System of High Power IGBT Modules

DEFF Research Database (Denmark)

Bahman, Amir Sajjad; Blaabjerg, Frede

2016-01-01

important issue for thermal design engineers. This paper aims to present a user friendly optimization tool for direct water cooling system of a high power module which enables the cooling system designer to identify the optimized solution depending on customer load profiles and available pump power. CFD...

Achieving informed decision-making for net zero energy buildings design using building performance simulation tools

NARCIS (Netherlands)

Attia, S.G.; Gratia, E.; De Herde, A.; Hensen, J.L.M.

2013-01-01

Building performance simulation (BPS) is the basis for informed decision-making of Net Zero Energy Buildings (NZEBs) design. This paper aims to investigate the use of building performance simulation tools as a method of informing the design decision of NZEBs. The aim of this study is to evaluate the

Optimal decision procedures for satisfiability in fragments of alternating-time temporal logics

DEFF Research Database (Denmark)

Goranko, Valentin; Vester, Steen

2014-01-01

We consider several natural fragments of the alternating-time temporal logics ATL*and ATL with restrictions on the nesting between temporal operators and strate-gicquantifiers. We develop optimal decision procedures for satisfiability in these fragments, showing that they have much lower complexi...

Multi-objective thermodynamic optimization of an irreversible regenerative Brayton cycle using evolutionary algorithm and decision making

OpenAIRE

Rajesh Kumar; S.C. Kaushik; Raj Kumar; Ranjana Hans

2016-01-01

Brayton heat engine model is developed in MATLAB simulink environment and thermodynamic optimization based on finite time thermodynamic analysis along with multiple criteria is implemented. The proposed work investigates optimal values of various decision variables that simultaneously optimize power output, thermal efficiency and ecological function using evolutionary algorithm based on NSGA-II. Pareto optimal frontier between triple and dual objectives is obtained and best optimal value is s...

Minimization of Decision Tree Average Depth for Decision Tables with Many-valued Decisions

KAUST Repository

Azad, Mohammad

2014-09-13

The paper is devoted to the analysis of greedy algorithms for the minimization of average depth of decision trees for decision tables such that each row is labeled with a set of decisions. The goal is to find one decision from the set of decisions. When we compare with the optimal result obtained from dynamic programming algorithm, we found some greedy algorithms produces results which are close to the optimal result for the minimization of average depth of decision trees.

Minimization of Decision Tree Average Depth for Decision Tables with Many-valued Decisions

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2014-01-01

The paper is devoted to the analysis of greedy algorithms for the minimization of average depth of decision trees for decision tables such that each row is labeled with a set of decisions. The goal is to find one decision from the set of decisions. When we compare with the optimal result obtained from dynamic programming algorithm, we found some greedy algorithms produces results which are close to the optimal result for the minimization of average depth of decision trees.

Decision modelling tools for utilities in the deregulated energy market

Energy Technology Data Exchange (ETDEWEB)

Makkonen, S. [Process Vision Oy, Helsinki (Finland)

2005-07-01

, strategic decision support has also faced new challenges. This thesis introduces two applications involving multiple criteria decision making methods. The first application explores the decision making problem caused by the introduction of 'green' electricity that creates additional value for renewable energy. In this problem the stochastic multicriteria acceptability analysis method (SMAA) is applied. The second strategic multi-criteria decision making study discusses two different energy-related operations research problems: the elements of risk analysis in the energy field and the evaluation of different choices with a decision support tool accommodating incomplete preference information to help energy companies to select a proper risk management system. The application is based on the rank inclusion in criteria hierarchies (RICH) method. (orig.)

A simulator-independent optimization tool based on genetic algorithm applied to nuclear reactor design

International Nuclear Information System (INIS)

Abreu Pereira, Claudio Marcio Nascimento do; Schirru, Roberto; Martinez, Aquilino Senra

1999-01-01

Here is presented an engineering optimization tool based on a genetic algorithm, implemented according to the method proposed in recent work that has demonstrated the feasibility of the use of this technique in nuclear reactor core designs. The tool is simulator-independent in the sense that it can be customized to use most of the simulators which have the input parameters read from formatted text files and the outputs also written from a text file. As the nuclear reactor simulators generally use such kind of interface, the proposed tool plays an important role in nuclear reactor designs. Research reactors may often use non-conventional design approaches, causing different situations that may lead the nuclear engineer to face new optimization problems. In this case, a good optimization technique, together with its customizing facility and a friendly man-machine interface could be very interesting. Here, the tool is described and some advantages are outlined. (author)

A method to assess how interactive water simulation tools influence transdisciplinary decision-making processes in water management

Science.gov (United States)

Leskens, Johannes

2015-04-01

In modern water management, often transdisciplinary work sessions are organized in which various stakeholders participate to jointly define problems, choose measures and divide responsibilities to take actions. Involved stakeholders are for example policy analysts or decision-makers from municipalities, water boards or provinces, representatives of pressure groups and researchers from knowledge institutes. Parallel to this increasing attention for transdisciplinary work sessions, we see a growing availability of interactive IT-tools that can be applied during these sessions. For example, dynamic flood risk maps have become recently available that allow users during a work sessions to instantaneously assess the impact of storm surges or dam breaches, displayed on digital maps. Other examples are serious games, realistic visualizations and participatory simulations. However, the question is if and how these interactive IT-tools contribute to better decision-making. To assess this, we take the process of knowledge construction during a work session as a measure for the quality of decision-making. Knowledge construction can be defined as the process in which ideas, perspectives and opinions of different stakeholders, all having their own expertise and experience, are confronted with each other and new shared meanings towards water management issues are created. We present an assessment method to monitor the process of knowledge construction during work sessions in water management in which interactive IT tools are being used. The assessment method is based on a literature review, focusing on studies in which knowledge construction was monitored in other contexts that water management. To test the applicability of the assessment method, we applied it during a multi-stakeholder work session in Westland, located in the southwest of the Netherlands. The discussions during the work session were observed by camera. All statements, expressed by the various members of a

Electricity Purchase Optimization Decision Based on Data Mining and Bayesian Game

Directory of Open Access Journals (Sweden)

Yajing Gao

2018-04-01

Full Text Available The openness of the electricity retail market results in the power retailers facing fierce competition in the market. This article aims to analyze the electricity purchase optimization decision-making of each power retailer with the background of the big data era. First, in order to guide the power retailer to make a purchase of electricity, this paper considers the users’ historical electricity consumption data and a comprehensive consideration of multiple factors, then uses the wavelet neural network (WNN model based on “meteorological similarity day (MSD” to forecast the user load demand. Second, in order to guide the quotation of the power retailer, this paper considers the multiple factors affecting the electricity price to cluster the sample set, and establishes a Genetic algorithm- back propagation (GA-BP neural network model based on fuzzy clustering (FC to predict the short-term market clearing price (MCP. Thirdly, based on Sealed-bid Auction (SA in game theory, a Bayesian Game Model (BGM of the power retailer’s bidding strategy is constructed, and the optimal bidding strategy is obtained by obtaining the Bayesian Nash Equilibrium (BNE under different probability distributions. Finally, a practical example is proposed to prove that the model and method can provide an effective reference for the decision-making optimization of the sales company.

A Diagnostics Tool to detect ensemble forecast system anomaly and guide operational decisions

Science.gov (United States)

Park, G. H.; Srivastava, A.; Shrestha, E.; Thiemann, M.; Day, G. N.; Draijer, S.

2017-12-01

The hydrologic community is moving toward using ensemble forecasts to take uncertainty into account during the decision-making process. The New York City Department of Environmental Protection (DEP) implements several types of ensemble forecasts in their decision-making process: ensemble products for a statistical model (Hirsch and enhanced Hirsch); the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) forecasts based on the classical Ensemble Streamflow Prediction (ESP) technique; and the new NWS Hydrologic Ensemble Forecasting Service (HEFS) forecasts. To remove structural error and apply the forecasts to additional forecast points, the DEP post processes both the AHPS and the HEFS forecasts. These ensemble forecasts provide mass quantities of complex data, and drawing conclusions from these forecasts is time-consuming and difficult. The complexity of these forecasts also makes it difficult to identify system failures resulting from poor data, missing forecasts, and server breakdowns. To address these issues, we developed a diagnostic tool that summarizes ensemble forecasts and provides additional information such as historical forecast statistics, forecast skill, and model forcing statistics. This additional information highlights the key information that enables operators to evaluate the forecast in real-time, dynamically interact with the data, and review additional statistics, if needed, to make better decisions. We used Bokeh, a Python interactive visualization library, and a multi-database management system to create this interactive tool. This tool compiles and stores data into HTML pages that allows operators to readily analyze the data with built-in user interaction features. This paper will present a brief description of the ensemble forecasts, forecast verification results, and the intended applications for the diagnostic tool.

A GIS-based generic real-time risk assessment framework and decision tools for chemical spills in the river basin.

Science.gov (United States)

Jiang, Jiping; Wang, Peng; Lung, Wu-seng; Guo, Liang; Li, Mei

2012-08-15

This paper presents a generic framework and decision tools of real-time risk assessment on Emergency Environmental Decision Support System for response to chemical spills in river basin. The generic "4-step-3-model" framework is able to delineate the warning area and the impact on vulnerable receptors considering four types of hazards referring to functional area, societal impact, and human health and ecology system. Decision tools including the stand-alone system and software components were implemented on GIS platform. A detailed case study on the Songhua River nitrobenzene spill illustrated the goodness of the framework and tool Spill first responders and decision makers of catchment management will benefit from the rich, visual and dynamic hazard information output from the software. Copyright © 2012 Elsevier B.V. All rights reserved.

Reward rate optimization in two-alternative decision making: empirical tests of theoretical predictions.

Science.gov (United States)

Simen, Patrick; Contreras, David; Buck, Cara; Hu, Peter; Holmes, Philip; Cohen, Jonathan D

2009-12-01

The drift-diffusion model (DDM) implements an optimal decision procedure for stationary, 2-alternative forced-choice tasks. The height of a decision threshold applied to accumulating information on each trial determines a speed-accuracy tradeoff (SAT) for the DDM, thereby accounting for a ubiquitous feature of human performance in speeded response tasks. However, little is known about how participants settle on particular tradeoffs. One possibility is that they select SATs that maximize a subjective rate of reward earned for performance. For the DDM, there exist unique, reward-rate-maximizing values for its threshold and starting point parameters in free-response tasks that reward correct responses (R. Bogacz, E. Brown, J. Moehlis, P. Holmes, & J. D. Cohen, 2006). These optimal values vary as a function of response-stimulus interval, prior stimulus probability, and relative reward magnitude for correct responses. We tested the resulting quantitative predictions regarding response time, accuracy, and response bias under these task manipulations and found that grouped data conformed well to the predictions of an optimally parameterized DDM.

Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

DEFF Research Database (Denmark)

Soares, João; Valle, Zita; Morais, Hugo

2013-01-01

This paper presents a decision support Tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy ressource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application...... of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network...... constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance...

Results from evaluations of models and cost-effectiveness tools to support introduction decisions for new vaccines need critical appraisal

Directory of Open Access Journals (Sweden)

Moorthy Vasee

2011-05-01

Full Text Available Abstract The World Health Organization (WHO recommends that the cost-effectiveness (CE of introducing new vaccines be considered before such a programme is implemented. However, in low- and middle-income countries (LMICs, it is often challenging to perform and interpret the results of model-based economic appraisals of vaccines that benefit from locally relevant data. As a result, WHO embarked on a series of consultations to assess economic analytical tools to support vaccine introduction decisions for pneumococcal, rotavirus and human papillomavirus vaccines. The objectives of these assessments are to provide decision makers with a menu of existing CE tools for vaccines and their characteristics rather than to endorse the use of a single tool. The outcome will provide policy makers in LMICs with information about the feasibility of applying these models to inform their own decision making. We argue that if models and CE analyses are used to inform decisions, they ought to be critically appraised beforehand, including a transparent evaluation of their structure, assumptions and data sources (in isolation or in comparison to similar tools, so that decision makers can use them while being fully aware of their robustness and limitations.

Multi-objective thermodynamic optimization of an irreversible regenerative Brayton cycle using evolutionary algorithm and decision making

Directory of Open Access Journals (Sweden)

Rajesh Kumar

2016-06-01

Full Text Available Brayton heat engine model is developed in MATLAB simulink environment and thermodynamic optimization based on finite time thermodynamic analysis along with multiple criteria is implemented. The proposed work investigates optimal values of various decision variables that simultaneously optimize power output, thermal efficiency and ecological function using evolutionary algorithm based on NSGA-II. Pareto optimal frontier between triple and dual objectives is obtained and best optimal value is selected using Fuzzy, TOPSIS, LINMAP and Shannon’s entropy decision making methods. Triple objective evolutionary approach applied to the proposed model gives power output, thermal efficiency, ecological function as (53.89 kW, 0.1611, −142 kW which are 29.78%, 25.86% and 21.13% lower in comparison with reversible system. Furthermore, the present study reflects the effect of various heat capacitance rates and component efficiencies on triple objectives in graphical custom. Finally, with the aim of error investigation, average and maximum errors of obtained results are computed.