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      Landfill site selection by integrating fuzzy logic, AHP, and WLC method based on multi-criteria decision analysis

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          How to make a decision: The analytic hierarchy process

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            Decision making with the analytic hierarchy process

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              Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average.

              This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process. Copyright © 2011 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Environmental Science and Pollution Research
                Environ Sci Pollut Res
                Springer Science and Business Media LLC
                0944-1344
                1614-7499
                April 2021
                January 06 2021
                April 2021
                : 28
                : 16
                : 19726-19741
                Article
                10.1007/s11356-020-11975-7
                33410005
                f7dd28aa-a393-4251-9a3d-2efcc427110b
                © 2021

                https://www.springer.com/tdm

                https://www.springer.com/tdm

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