Optimal Selection of Construction Schemes Based on Simplified ELECTRE

Bian, Jing Mei; Bai, Qingsheng

doi:10.4028/www.scientific.net/amr.616-618.332

Cited by 1 publication

(1 citation statement)

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“…Despite these differences, there are three major common steps; namely, normalizing the decision matrix, weighting the normalized decision matrix, and determining the concordance and the discordance [87,94,95]. However, for ease of analysis, the three steps can be subdivided into several smaller steps [93,96,97]. This study employed eight steps to apply ELECTRE: (1) organizing elements for initial computation, (2) standardizing elements of the initial decision matrix, (3) weighing the standardized decision matrix to construct outranking relationships, (4) constructing matrices of concordance and discordance, (5) constructing a discordance index, (6) setting concordance and discordance thresholds, (7) constructing matrices of concordant and discordant dominance, and (8) constructing a matrix of aggregate dominance.…”

Section: Methodsmentioning

confidence: 99%

Analyzing Municipal Solid Waste Treatment Scenarios in Rapidly Urbanizing Cities in Developing Countries: The Case of Dar es Salaam, Tanzania

Kazuva

Zhang

2019

IJERPH

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Currently, large quantities of municipal solid waste (MSW) in many cities of the developing countries are being dumped in informal or formal but unregulated dumpsites that threaten the ecological environment and general public health. The situation in Dar es Salaam, Tanzania is of particular concern and is further challenged by a rapidly growing population and urbanization without adequate waste management systems. Current MSW treatment options have been selected based on the judgment and the experience of individuals with authority while underestimating the role of scientifically derived techniques. This study analyzes the most efficient waste treatment options, particularly scenarios with the lowest economic and environmental costs (EcC and EnC, respectively). It uses 12 years (2006–2017) of MSW management data and compares potential waste treatment options for the identified waste streams. A total of 108 different scenarios were designed, and a multi-criteria analysis method was applied to enable the identification of 11 scenarios with acceptable EcCs and EnCs. These formed an initial decision matrix of aggregation dominance that was then categorized into four groups, each represented by the most ideal point. Finally, the dominant scenario that formed the core for all considered options was found. It costs around $274,100 USD while saving about 1585 metric tons (MT) of CO2 emissions daily. This suggests that after all the MSW generated in the city is collected and segregated, organic waste should be composted whilst plastic, paper, glass, and ferrous metal should be recycled. After treatment, other waste will go to some form of landfill. Sustainable management of MSW in this city and others with similar conditions should consider particular local conditions and could use the methods and the findings of this study as a starting point.

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