A multi-objective decision support framework to prioritize tree planting locations in urban areas

2021 ◽  
Vol 214 ◽  
pp. 104172
Author(s):  
Charity Nyelele ◽  
Charles N. Kroll
2006 ◽  
Vol 54 (6-7) ◽  
pp. 451-458 ◽  
Author(s):  
C.K. Makropoulos ◽  
M. Morley ◽  
F.A. Memon ◽  
D. Butler ◽  
D. Savic ◽  
...  

The paper discusses issues of decision support within the context of sustainable development and more specifically sustainable water cycle management to provide a context and a rationale for the decision support approach adopted within an on-going UK EPSRC-funded project, WaND. The paper proposes a set-up for a flexible, upgradeable, efficient and modular decision support framework and associated tools. Furthermore, the paper presents early prototypes of three decision support tools developed within the proposed framework including initial results for one of them.


2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.


2015 ◽  
Author(s):  
L. K. Kirkman ◽  
John K. Hiers A. ◽  
L. L. Smith ◽  
L. M. Conner ◽  
S. L. Zeigler ◽  
...  

2021 ◽  
Vol 55 (5) ◽  
pp. 2890-2898 ◽  
Author(s):  
Tami C. Bond ◽  
Angela Bosco-Lauth ◽  
Delphine K. Farmer ◽  
Paul W. Francisco ◽  
Jeffrey R. Pierce ◽  
...  

Author(s):  
David Kik ◽  
Matthias Gerhard Wichmann ◽  
Thomas Stefan Spengler

AbstractLocation choice is a crucial planning task with major influence on a company’s future orientation and competitiveness. It is quite complex, since multiple location factors are usually of decision-relevance, incomparable, and sometimes conflictual. Further, ongoing urbanization is associated with locational dynamics posing major challenges for the regional location management of companies and municipalities. For example, respecting urban space as location factor, a scarcity growing over time leads to different assessment and requirements on a company’s behalf. For both companies and municipalities, there is a need for location development which implies an active change of location factor characteristics. Accordingly, considering locational dynamics is vital, as they may be decisive in the location decision-making. Although certain dynamics are considered within conventional Facility Location Problem (FLP) approaches, a systematic consideration of active location development is missing so far. Consequently, they may propagate long-term unfavorable location decisions, as major potentials associated with company-driven and municipal development measures are neglected. Therefore, this paper introduces a comprehensive decision support framework for the Regional Facility Location and Development planning Problem (RFLDP). It provides an operationalization of development measures, and thus anticipates dynamic adaptations to the environment. An established multi-criteria approach is extended to this new application. A complementary guideline ensures its meaningful applicability by practitioners. Based on a real-life case study, the decision support framework’s strength for practical application is demonstrated. Here, major advantages over conventional FLP approaches are highlighted. It is shown that the proposed methodology results in alternative location decisions which are structurally superior.


1999 ◽  
Vol 69 (1-2) ◽  
pp. 31-42
Author(s):  
D. Deligiorgi ◽  
C. Cartalis ◽  
G. Kouroupetroglou ◽  
C. Moutselos ◽  
E. Kambitsi

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