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

‘PLATE’: A decision support system for resource constrained scheduling problems

1994 ◽  
Vol 79 (2) ◽  
pp. 158-166 ◽  
Author(s):  
A.T.M. Aerts ◽  
A. Jansen ◽  
L. Klieb ◽  
C. Noorlander ◽  
G. Wolf
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Scheduling Problems ◽  
Resource Constrained

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.

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.

Development of a Decision Support System in Ship-To-Ship Lightering

2016 ◽  
Vol 69 (5) ◽  
pp. 1154-1182 ◽  
Author(s):  
Dagfinn Husjord
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Work Environment ◽  
Support System ◽  
Situation Awareness ◽  
Interaction Design ◽  
Performance Test ◽  
Real Life ◽  
Ship Handling

This paper focusses on the development of a tool for decision-making, tailored for personnel involved in complex Ship-To-Ship (STS) operations, to enhance the efficiency and safety of these operations. A step-wise approach has been selected. The first step includes specification, development and testing of the tool in a simulated work environment using full-mission simulators. In the second step the findings from application of the tool in the simulated work environment will be used to develop a prototype which will be tested during real life STS operations. This paper describes work done in the first of these two steps. During four iterations, a Graphical User Interface (GUI) has been made following Interaction Design (IxD) principles. The designs have been iteratively developed and tested by experienced ship's officers in a ship-handling simulator to clarify key information to enhance their Situation Awareness (SA) and decision-making process. In order to find indicators for performance, an initial performance test was carried out in a ship-handling simulator. The test indicates that a logic based Decision-Support System (DSS) can improve existing simulator-based training activities in STS operations.

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