scholarly journals Decision support system for the long-term city metabolism planning problem

2015 ◽  
Vol 16 (2) ◽  
pp. 542-550 ◽  
Author(s):  
M. S. Morley ◽  
D. Vitorino ◽  
K. Behzadian ◽  
R. Ugarelli ◽  
Z. Kapelan ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
User Interfaces ◽  
Performance Metrics ◽  
Real Life ◽  
Water System ◽  
Planning Horizon ◽  
Planning Problem

A decision support system (DSS) tool for the assessment of intervention strategies (Alternatives) in an urban water system (UWS) with an integral simulation model called ‘WaterMet2’ is presented. The DSS permits the user to identify one or more optimal Alternatives over a fixed long-term planning horizon using performance metrics mapped to the TRUST sustainability criteria. The DSS exposes lists of in-built intervention options and system performance metrics for the user to compose new Alternatives. The quantitative metrics are calculated by the WaterMet2 model, and further qualitative or user-defined metrics may be specified by the user or by external tools feeding into the DSS. A multi-criteria decision analysis approach is employed within the DSS to compare the defined Alternatives and to rank them with respect to a pre-specified weighting scheme for different Scenarios. Two rich, interactive graphical user interfaces, one desktop and one web-based, are employed to assist with guiding the end user through the stages of defining the problem, evaluating and ranking Alternatives. This mechanism provides a useful tool for decision makers to compare different strategies for the planning of UWS with respect to multiple Scenarios. The efficacy of the DSS is demonstrated on a northern European case study inspired by a real-life UWS for a mixture of quantitative and qualitative criteria. The results demonstrate how the DSS, integrated with an UWS modelling approach, can be used to assist planners in meeting their long-term, strategic-level sustainability objectives.

A decision support system that links short-term silvicultural operating plans with long-term forest-level strategic plans

1993 ◽  
Vol 23 (6) ◽  
pp. 1078-1095 ◽  
Author(s):  
Robert G. Davis ◽  
David L. Martell
Keyword(s):  
Information System ◽  
Decision Support ◽  
Decision Support System ◽  
Geographical Information System ◽  
Support System ◽  
Planning Horizon ◽  
Geographical Information ◽  
Timber Species ◽  
Short Term

This paper describes a decision support system that forest managers can use to help evaluate short-term, site-specific silvicultural operating plans in terms of their potential impact on long-term, forest-level strategic objectives. The system is based upon strategic and tactical forest-level silvicultural planning models that are linked with each other and with a geographical information system. Managers can first use the strategic mathematical programming model to develop broad silvicultural strategies based on aggregate timber strata. These strategies help them to subjectively delineate specific candidate sites that might be treated during the first 10 years of a much longer planning horizon using a geographical information system and to describe potential silvicultural prescriptions for each candidate site. The tactical model identifies an annual silvicultural schedule for these candidate sites in the first 10 years, and a harvesting and regeneration schedule by 10-year periods for aggregate timber strata for the remainder of the planning horizon, that will maximize the sustainable yield of one or more timber species in the whole forest, given the candidate sites and treatments specified by the managers. The system is demonstrated on a 90 000 - ha area in northeastern Ontario.

scholarly journals Decision support system for metabolism-based transition to urban water systems of tomorrow

2016 ◽  
Vol 16 (3) ◽  
pp. 855-863 ◽  
Author(s):  
Mark Morley ◽  
Kourosh Behzadian ◽  
Zoran Kapelan ◽  
Rita Ugarelli
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Real Life ◽  
Water System ◽  
Intervention Strategies ◽  
Urban Water ◽  
Urban Water System ◽  
Northern European ◽  
And Performance

A decision support system (DSS) tool for the assessment of intervention strategies in an urban water system (UWS) with an integral simulation model called ‘WaterMet2’ is presented. Lists of intervention options and performance indicators are exposed by the DSS for the user to define intervention strategies and metrics for their comparison. The quantitative and risk-based metrics are calculated by WaterMet2 and risk modules, while the qualitative metrics may be quantified by external tools feeding into the DSS. Finally, a multi-criteria decision analysis approach is employed in the DSS to compare the defined intervention strategies and rank them with respect to a pre-specified weighting scheme for different scenarios. This mechanism provides a useful tool for decision makers to compare different strategies for the planning of UWS with respect to multiple scenarios. The suggested DSS is demonstrated through the application to a northern European real-life case study.

scholarly journals Model Predictive Control of a River Reach with Weirs

10.29007/1nnf ◽  
2018 ◽  
Author(s):  
Klaudia Horváth ◽  
Bart van Esch ◽  
Jorn Baayen ◽  
Ivo Pothof ◽  
Jan Talsma ◽  
...  
Keyword(s):  
Decision Support ◽  
Convex Optimization ◽  
Decision Support System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Support System ◽  
Water System ◽  
Open Water ◽  
Global Optimum ◽  
Water Levels

A decision support system for water management based on convex optimization, RTC-Tools 2, is applied for a water system containing river branches connected by weirs. The advantage of convex optimization is the ability of finding the global optimum, which makes the decision support system robust and deterministic. In this work the convex modeling of open water channels and weirs is presented. The decision support system is implemented for a river made of 12 river reaches divided by movable weirs. It is shown how the discharge wave is dispatched in the river without the water levels exceeding the bounds by controlling the weir heights. After this test the optimization can be applied to a realistic numerical model and model predictive control can be implemented.

scholarly journals Decision Support System for Green Real-Life Field Scheduling Problems

2017 ◽  
pp. 355-369
Author(s):  
Yizi Zhou ◽  
Anne Liret ◽  
Jiyin Liu ◽  
Emmanuel Ferreyra ◽  
Rupal Rana ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Real Life ◽  
Scheduling Problems

Bidder Selection in Public Procurement using a Fuzzy Decision Support System

Fuzzy Systems ◽  
2017 ◽  
pp. 1620-1642
Author(s):  
Vjekoslav Bobar ◽  
Ksenija Mandic ◽  
Milija Suknovic
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Public Procurement ◽  
Real Life ◽  
Case Scenario ◽  
Uncertain Variables ◽  
Public Money ◽  
Fuzzy Extent Analysis ◽  
The Cost

Bidder selection in public procurement is a decision making problem whose primary purpose is to achieve the cost effectiveness and efficiency in the expenditure of public money. This principle is also known as the principle of “value for money”. This selection is based on many alternatives and many quantitative and qualitative criteria where qualitative criteria are often expressed as linguistic uncertain variables. The theory of fuzzy sets is a tool suitable to model uncertainty when applied to a variety of problems in real life. However, many fuzzy methods require complex calculation and they are not appropriate for using in public procurement because they slow down this process. In this paper, in order to make a quick decision in public procurement, a Decision Support System based on the fuzzy extent analysis method is developed. In order to demonstrate the usefulness of this system, a real-life case scenario of public procurement is presented.

scholarly journals Decision Support System for Daily and Long Term Operations of the System of Milan, Italy

2016 ◽  
Vol 154 ◽  
pp. 58-61 ◽  
Author(s):  
Quan Pan ◽  
Mario Erik Castro-Gama ◽  
Andreja Jonoski ◽  
Ioana Popescu
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System

Bidder Selection in Public Procurement using a Fuzzy Decision Support System

2015 ◽  
Vol 7 (1) ◽  
pp. 31-49 ◽  
Author(s):  
Vjekoslav Bobar ◽  
Ksenija Mandic ◽  
Milija Suknovic
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Public Procurement ◽  
Real Life ◽  
Case Scenario ◽  
Uncertain Variables ◽  
Public Money ◽  
Fuzzy Extent Analysis ◽  
The Cost

Bidder selection in public procurement is a decision making problem whose primary purpose is to achieve the cost effectiveness and efficiency in the expenditure of public money. This principle is also known as the principle of “value for money”. This selection is based on many alternatives and many quantitative and qualitative criteria where qualitative criteria are often expressed as linguistic uncertain variables. The theory of fuzzy sets is a tool suitable to model uncertainty when applied to a variety of problems in real life. However, many fuzzy methods require complex calculation and they are not appropriate for using in public procurement because they slow down this process. In this paper, in order to make a quick decision in public procurement, a Decision Support System based on the fuzzy extent analysis method is developed. In order to demonstrate the usefulness of this system, a real-life case scenario of public procurement is presented.

Evaluation of a computational decision support system for molecularly targeted treatment planning by the clinical outcome data of the randomized trial SHIVA01.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 3642-3642
Author(s):  
Anna Dirner ◽  
Robert Doczi ◽  
Peter Filotas ◽  
Barbara Vodicska ◽  
Edit Varkondi ◽  
...  
Keyword(s):  
Decision Support ◽  
Targeted Therapy ◽  
Decision Support System ◽  
Support System ◽  
Clinical Decision Making ◽  
Real Life ◽  
Molecular Profile ◽  
Evidence Based ◽  
Precision Oncology ◽  
Molecular Profiles

3642 Background: Precision oncology requires the identification of individual molecular pathomechanisms to find optimal personalized treatment strategies for every cancer patient. Incorporation of complex molecular information into routine clinical practice remains a significant challenge due to the lack of a reproducible, standardized process of clinical decision making. Methods: To provide a standardized process for molecular interpretation, we develop a precision oncology decision support system, the Realtime Oncology Molecular Treatment Calculator (MTC). MTC is a rule-based medical knowledge engine that dynamically aggregates and ranks relevant scientific and clinical evidence using currently 26,000 evidence-based associations and reproducible algorithm scoring of drivers, molecular targets to match molecular alterations to efficient therapies. To validate this novel method and system, we used data of the SHIVA01 trial of molecularly targeted therapy (Lancet Oncol 2015 16:1324-34). Molecular profiles of participants were uploaded to MTC and aggregated evidence level (AEL) values of associated targeted treatments were calculated, including those used in the SHIVA01 trial. Results: The MTC output provided a prioritized list of drugs associated with the driver alterations in the patient molecular profile, where ranking is based on AEL values. Of 113 patients who received targeted therapy with available clinical best response data, disease control was experienced in 63 cases (PR: 5, SD: 58), while disease progression occurred in 50 cases. The average AEL score for the therapies applied was significantly higher in the responsive group than in the non-responsive group (1512 and 614, respectively (p = 0.049)). In 94 cases, drugs other than those used for therapy were ranked higher by the MTC. The average AEL difference between the top-ranked and the used drugs was in an inverse correlation with clinical response, i.e. smaller differences associated with a better outcome. Conclusions: Results indicate that the aggregation of evidence-based tumor-driver-target-drug associations using standardized mathematical algorithms of this computational tool is a promising novel approach to improve clinical decisions in precision oncology. Further validation based on the results of other targeted clinical trials and real-life data using more detailed molecular profiles is warranted to explore the full clinical potential of this novel medical solution.

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