2016
DOI: 10.1111/jiec.12467
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Location Optimization of Urban Mining Facilities with Maximal Covering Model in GIS: A Case of China

Abstract: Urban mining offers an efficient supply of resources because of rich mines and low environmental impacts. Location selection and optimization for urban mining facilities is more complicated than for natural mines, given that it may vary according to the urban population, consumption habits, and economic development. China initiated the National Urban Mining Pilot Bases program in 2010 that targeted 50 national urban mining pilot bases, but unfortunately neglected the location planning issue. Twenty-eight bases… Show more

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Cited by 17 publications
(12 citation statements)
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References 34 publications
(39 reference statements)
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“…Previous studies on waste management efficiency (such as the recycling rate) have focused on socio-economic factors (e.g., GDP per capita and economic size), demographic characteristics (e.g., population density), technology levels, household-related socioeconomic factors (e.g., household participation rates, education, financial status, etc.) [56], and waste management systems [57][58][59].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Previous studies on waste management efficiency (such as the recycling rate) have focused on socio-economic factors (e.g., GDP per capita and economic size), demographic characteristics (e.g., population density), technology levels, household-related socioeconomic factors (e.g., household participation rates, education, financial status, etc.) [56], and waste management systems [57][58][59].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Comber et al (2015) used the GIS to customize the classic p-median problem. Xue et al (2017) used the GIS for locating the optimum location of the urban facilities considering the maximal covering issues. Zhang et al (2017) applied a hybrid approach for bio-ethanol facility location for minimizing the total cost by integrating the GIS and mathematical programming techniques.…”
Section: Literature Review and Research Gapmentioning
confidence: 99%
“…LINGO / GA Temur and Yanik [207] 2017 exact / heur GAMS + CPLEX / Cloud Based Design Optimization (CBDO) Uster and Hwang [128] 2017 exact CPLEX, enhanced BD Wang et al [181] 2017 heur. Plant Growth Simulation Algorithm Xu et al [187] 2017 exact GAMS + CPLEX Xu et al [153] 2017 exact IBM ILOG CPLEX Optimization Studio Xue et al [290] 2017 exact GIS Yu and Solvang [105] 2017 exact LINGO Zhao and Ke [263] 2017 exact CPLEX…”
mentioning
confidence: 99%