scholarly journals Development and Application of a Multi-Objective-Optimization and Multi-Criteria-Based Decision Support Tool for Selecting Optimal Water Treatment Technologies in India

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2836
Author(s):  
Seyed M. K. Sadr ◽  
Matthew B. Johns ◽  
Fayyaz A. Memon ◽  
Andrew P. Duncan ◽  
James Gordon ◽  
...  

Despite considerable efforts to improve water management, India is becoming increasingly water stressed due to multiple factors, including climate change, increasing population, and urbanization. We address one of the most challenging problems in the design of water treatment plants: how to select a suitable technology for a specific scenario or context. The process of decision making first requires the identification of feasible treatment configurations based on various objectives and criteria. In addition, the multiplicity of water quality parameters and design variables adds further complexity to the process. In this study, we propose a novel Decision Support Tool (DST), designed to address and support the above challenges. In this user-friendly tool, both Multi-Criteria Decision Analysis (MCDA) and Multi-Objective Optimization (MOO) methods are employed. The integration of MCDA with MOO facilitates the generation of feasible drinking water treatment solutions, identifies optimal options, and ultimately, improves the process of decision making. This implemented approach has been tested for different contexts, including for different types of raw water sources and system implementation scales. The results show that this tool can enhance the process of decision making, supporting the user (e.g., stakeholders and decision makers) to implement the most suitable water treatment systems, keeping in view the trade-offs.

2013 ◽  
Vol 52 (22-24) ◽  
pp. 4079-4088 ◽  
Author(s):  
Bouchra Lamrini ◽  
El Khadir Lakhal ◽  
Marie Véronique Le Lann

2014 ◽  
Vol 27 (1) ◽  
pp. 94-106 ◽  
Author(s):  
David Mark McKevitt ◽  
Anthony Flynn ◽  
Paul Davis

Purpose – The aim of this paper is to explore the factors that influence buyer decision-making in public procurement. The objective is to better understand the processes and conditions that support different supply arrangements, which maximise SME participation. Design/methodology/approach – The paper uses case study evidence of contract awards across multiple organisational contexts including: a local authority, commercial semi-state, police force, and a tourist agency. Findings – National policy and the role of procurement exerted mixed effects upon the cases. The procurement processes were broadly similar and included cross-functional teams, consideration of trade-offs and market research. Research limitations/implications – The paper highlights the transition of public organisations toward strategic procurement including supplier engagement. Practical implications – This offers buyers a decision support tool that promotes equal opportunities for SME participation, a key goal of EU procurement. The implications for suppliers of each buying decision are also outlined. The concept of practical rationality is used to support the framework. Originality/value – A normative framework of public procurement decision-making is generated from the cases. Buying complexity and supplier engagement are two conditions that support a 2×2 decision framework. The framework extends efficient and central-buying decisions to include adapted and balanced decisions. This range offers buyers a decision support tool that promotes equal opportunities for SME participation, a key goal of EU procurement. The implications for suppliers of each buying decision are discussed.


2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Natasha Michael ◽  
Clare O’Callaghan ◽  
Ekavi Georgousopoulou ◽  
Adelaide Melia ◽  
Merlina Sulistio ◽  
...  

Abstract Background Views on advance care planning (ACP) has shifted from a focus solely on treatment decisions at the end-of-life and medically orientated advanced directives to encouraging conversations on personal values and life goals, patient-caregiver communication and decision making, and family preparation. This study will evaluate the potential utility of a video decision support tool (VDST) that models values-based ACP discussions between cancer patients and their nominated caregivers to enable patients and families to achieve shared-decisions when completing ACP’s. Methods This open-label, parallel-arm, phase II randomised control trial will recruit cancer patient-caregiver dyads across a large health network. Previously used written vignettes will be converted to video vignettes using the recommended methodology. Participants will be ≥18 years and be able to complete questionnaires. Dyads will be randomised in a 1:1 ratio to a usual care (UC) or VDST group. The VDST group will watch a video of several patient-caregiver dyads communicating personal values across different cancer trajectory stages and will receive verbal and written ACP information. The UC group will receive verbal and written ACP information. Patient and caregiver data will be collected individually via an anonymous questionnaire developed for the study, pre and post the UC and VDST intervention. Our primary outcome will be ACP completion rates. Secondarily, we will compare patient-caregiver (i) attitudes towards ACP, (ii) congruence in communication, and (iii) preparation for decision-making. Conclusion We need to continue to explore innovative ways to engage cancer patients in ACP. This study will be the first VDST study to attempt to integrate values-based conversations into an ACP intervention. This pilot study’s findings will assist with further refinement of the VDST and planning for a future multisite study. Trial registration Australian New Zealand Clinical Trials Registry No: ACTRN12620001035910. Registered 12 October 2020. Retrospectively registered.


Author(s):  
Dawn M. Magnusson ◽  
Irena Shwayder ◽  
Natalie J. Murphy ◽  
Lindsay Ollerenshaw ◽  
Michele Ebendick ◽  
...  

Purpose Despite increasing standardization of developmental screening and referral processes, significant early intervention service disparities exist. The aims of this article are to: (a) describe methods used to develop a decision support tool for caregivers of children with developmental concerns, (b) summarize key aspects of the tool, and (c) share preliminary results regarding the tool's acceptability and usability among key stakeholders. Method Content and design of the decision support tool was guided by a systematic process outlined by the International Patient Decision Aid Standards (IPDAS) Collaborative. Three focus group interviews were conducted with caregivers ( n = 7), early childhood professionals ( n = 28), and a mix of caregivers and professionals ( N = 20) to assess caregiver decisional needs. In accordance with the IPDAS, a prototype of the decision support tool was iteratively cocreated by a subset of caregivers ( n = 7) and early child health professionals ( n = 5). Results The decision support tool leverages images and plain language text to guide caregivers and professionals along key steps of the early identification to service use pathway. Participants identified four themes central to shared decision making: trust, cultural humility and respect, strength-based conversations, and information-sharing. End-users found the tool to be acceptable and useful. Conclusions The decision support tool described offers an individualized approach for exploring beliefs about child development and developmental delay, considering service options within the context of the family's values, priorities, and preferences, and outlining next steps. Additional research regarding the tool's effectiveness in optimizing shared decision-making and reducing service use disparities is warranted.


2019 ◽  
Vol 109 (03) ◽  
pp. 134-139
Author(s):  
P. Burggräf ◽  
J. Wagner ◽  
M. Dannapfel ◽  
K. Müller ◽  
B. Koke

Der wachsende Bedarf an Wandlungsfähigkeit führt zu einer höheren Frequenz in der Umplanung von Montagesystemen und erfordert eine kontinuierliche Überprüfung und Anpassung des Automatisierungsgrades. Um auch die komplexen Umgebungsbedingungen abzubilden, sollen nicht-monetäre Faktoren in den Entscheidungsprozess eingebunden werden. Um die Entscheidung zu unterstützen, stellt dieser Beitrag ein Tool zur Identifizierung und Bewertung von Automatisierungsszenarien mittels einer Nutzwert-Aufwand-Analyse vor.   The increasing need for adaptability in assembly leads to a higher planning frequency of the system and requires continuous checks and adaptations of the appropriate level of automation. To account for the complex environmental conditions, non-monetary factors are included in the decision-making process. This paper presents a decision support tool to identify and evaluate automation scenarios by means of cost and benefit evaluation.


Author(s):  
Cristina Johansson ◽  
Johan Ölvander ◽  
Micael Derelöv

In early design phases, it is vital to be able to screen the design space for a set of promising design alternatives for further study. This article presents a method able to balance several objectives of different mathematical natures, with high impact on the design choices. The method (MOSART) handles multi-objective optimization for safety and reliability trade-offs. The article focuses on optimization problem approach and processing of results as a base for decision-making. The output of the optimization step is the selection of specific system elements obtaining the best balance between the targets. However, what is a good base for decision can easily transform into too much information and overloading of the decision-maker. To solve this potential issue, from a set of Pareto optimal solutions, a smaller sub-set of selected solutions are visualized and filtered out using preference levels of the objectives, yielding a solid base for decision-making and valuable information on potential solutions. Trends were observed regarding each system element and discussed while processing the results of the analysis, supporting the decision of one final best solution.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Serhat Simsek ◽  
Abdullah Albizri ◽  
Marina Johnson ◽  
Tyler Custis ◽  
Stephan Weikert

PurposePredictive analytics and artificial intelligence are perceived as significant drivers to improve organizational performance and managerial decision-making. Hiring employees and contract renewals are instances of managerial decision-making problems that can incur high financial costs and long-term impacts on organizational performance. The primary goal of this study is to identify the Major League Baseball (MLB) free agents who are likely to receive a contract.Design/methodology/approachThis study used the design science research paradigm and the cognitive analytics management (CAM) theory to develop the research framework. A dataset on MLB's free agents between 2013 and 2017 was collected. A decision support tool was built using artificial neural networks.FindingsThere are clear links between a player's statistical performance and the decision of the player to sign a new offered contract. “Age,” “Wins above Replacement” and “the team on which a player last played” are the most significant factors in determining if a player signs a new contract.Originality/valueThis paper applied analytical modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers in baseball front offices so they can determine which available free agents to offer contracts.


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