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Multiple Criteria Decision Analysis Using Dea-Topsis Method For Hazardous Waste Management: A Case Study Of Usa

Authors: Mohsin Ali1;

Multiple Criteria Decision Analysis Using Dea-Topsis Method For Hazardous Waste Management: A Case Study Of Usa

Abstract

Environmental pollution is one of the major concerns in the recent world. Hazardous waste is the major factors causing pollution and degradation of environment. It is such waste with a chemical composition or other properties that make it capable of causing harm to humans and other life forms when mishandled or released into the environment. USA (United State of America)is developed country but facing tough time to secure the life from hazardous waste. Dealing with such problem is not easy task for the hazardous waste management officers because all parties have their own opinion and views which is difficult to put all together at once. Even it is tough task to gratify all concern parties but researcher always try to come up with new proposal so that can be beneficial for the present improvement and future decision making. This paper adopts MCDA (multiple criteria decision analysis) for analysis of hazardous waste in the USA. MCDA proposed DEA-TOPSIS (data envelopment analysis – technique for order performance by similarity to ideal solution) hybrid approach for findings of hazardous waste. MCDA helps in solving decision making problems in various sectors such as corporate, social and environmental issues. This paper will help EPA (environmental protection agency) to improve hazardous waste in different states while comparing with the best one.

Keywords

Hazardous Waste, MCDA, DEA-TOPSIS, EPA, USA

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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