2019
DOI: 10.3390/su11143904
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An Optimisation Model to Consider the NIMBY Syndrome within the Landfill Siting Problem

Abstract: This paper proposes a discrete optimisation model and a heuristic algorithm to solve the landfill siting problem over large areas. Besides waste transport costs and plant construction and maintenance costs, usually considered in such problems, the objective function includes economic compensation for residents in the areas affected by the landfill, to combat the NIMBY (Not In My Back Yard) syndrome or, at least, reduce its adverse effects. The proposed methodology is applied to a real-scale case study, the reg… Show more

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Cited by 15 publications
(8 citation statements)
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“…This discriminatory practice can be shown as the power-play of urban elites who do not wish to manage their waste in their own backyard, instead, they dump their waste to locations where socio-economically disadvantaged sections of the society reside. This tendency is termed as "Not in my backyard" (NIMBY), which can be defined as a widespread phenomenon related to the strong opposition of a community to some publicinterest interventions in a local area, mainly "undesirable plants", such as landfills, incinerators and thermoelectric power plants [19,20].…”
Section: • Reduced Storage Of Biodegradable Wastementioning
confidence: 99%
“…This discriminatory practice can be shown as the power-play of urban elites who do not wish to manage their waste in their own backyard, instead, they dump their waste to locations where socio-economically disadvantaged sections of the society reside. This tendency is termed as "Not in my backyard" (NIMBY), which can be defined as a widespread phenomenon related to the strong opposition of a community to some publicinterest interventions in a local area, mainly "undesirable plants", such as landfills, incinerators and thermoelectric power plants [19,20].…”
Section: • Reduced Storage Of Biodegradable Wastementioning
confidence: 99%
“…Cong et al found that near the place of residence was one of the crucial factors that resulted in site selection failure [7]. Gallo used a discrete optimisation model and a heuristic algorithm to solve the landfill siting problem and suggested that landfills should be located in sparsely populated sites [51]. Sun et al found that the closer the distance between waste-to-energy plants and the real estate, the stronger the negative externality of waste-toenergy plants [52].…”
Section: Indicators Of Public Risk Perceptionmentioning
confidence: 99%
“…Gu et al (2017) [15] fully considered the impact of external effects on the location of waste power plants, and established a bi-level planning model to optimize the location of waste power plants in Wuhan. Gallo (2019) [16] proposes a discrete optimization model and a heuristic algorithm to solve the landfill siting problem over large areas. Zhao and Huang (2019) [17] explored the multi-period network design problem is to determine the location of waste facilities in each period during the planning horizon.…”
Section: Relevant Nimby Facilities Location Modelsmentioning
confidence: 99%