A life cycle based multi-objective optimization model for the management of computer waste

Ahluwalia, Poonam; Nema, Arvind K.

doi:10.1016/j.resconrec.2007.01.001

Cited by 64 publications

(31 citation statements)

References 21 publications

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“…Besides economic evaluation of the recycling option, which requires both energy and resources, product Life Cycle Assessment (LCA) is an important tool to envisage the environmental and resource consequences for the sustainable development. Since the end of 1990s, a number of models for integrated waste management including E-waste management have been proposed based on the LCA (Ahluwalia and Nema, 2007;Andrae and Andersen, 2010;Duan et al, 2009;Finnveden et al, 1995;Harrison et al, 2001;Winkler and Bilitewski, 2007). Hula et al (2003) demonstrated multi-criteria analysis (MCA) method to determine the economics and environmental benefits from material recovery based on the product structure, materials, location of recycling facilities, applicable regulations, geography as well as cultural context.…”

Section: Issues and Scopesmentioning

confidence: 99%

Waste Printed Circuit Boards recycling: an extensive assessment of current status

Ghosh

Parhi

et al. 2015

Journal of Cleaner Production

482

180

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Section: Issues and Scopesmentioning

confidence: 99%

Waste Printed Circuit Boards recycling: an extensive assessment of current status

Ghosh

Parhi

et al. 2015

Journal of Cleaner Production

482

180

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“…The segment-based crossover is applied to generate new chromosomes from the population (Ahluwalia and Nema, 2007). In the developed model, 30 segments considered for collection centre and 30 * 4 segments represents the recovery plants.…”

Section: Step 2: Crossovermentioning

confidence: 99%

Designing a sustainable recovery network for waste from electrical and electronic equipment using a genetic algorithm

Shokouhyar

Aalirezaei

2017

IJESD

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Abstract:In recent years, reverse logistic and closed-loop supply chain issues have became more important due to environmental, social and economic reasons. Product recovery which comprises recycling, remanufacturing, repairing and disposing requires an efficient reverse logistic network. Among used products, waste electrical and electronic equipment (WEEE) has become a major problem for developing countries due to its harmful effects. WEEE contains hazardous materials that may have an impact on both environment and human health if it is properly managed. On the contrary, valuable materials can be extracted if it is controlled properly. Therefore, decision makers should give consideration to design an efficient reverse logistic network to manage WEEE. In this paper, a mathematical model of two-stage RL network has been developed based on sustainable development objectives in which economic, environmental and social objectives are considered simultaneously. A multi objective genetic algorithm (MOGA) is developed to determine the best locations of collection centres and recycling plants. In result, the decision makers can make the trade-off between environmental issues and economic and social impacts. The proposed model is examined through a real case from Iran's WEEE current situation.Keywords: reverse logistic network; multi objective genetic algorithm; MOGA; none dominated sorting genetic algorithm-II; NSGA-II; waste electrical and electronic equipment; WEEE; sustainable development.Reference to this paper should be made as follows: Shokouhyar, S. and Aalirezaei, A. (2017) 'Designing a sustainable recovery network for waste from electrical and electronic equipment using a genetic algorithm', Int.

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“…These methods are included in a waste hierarchy which is accepted as a universal guideline for waste management in many countries (Ahluwalia, Nema 2007;Ghinea, Gavrilescu 2010a;Kirkeby 2005).…”

Section: Development Of the Mswm Scenariosmentioning

confidence: 99%

Costs Analysis of Municipal Solid Waste Management Scenarios: Iasi – Romania Case Study

Ghinea

Gavrilescu

2016

Journal of Environmental Engineering and Landscape Management

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Abstract. Trinitrotoluene (TNT), a commonly used explosive for military and industrial applications, can cause serious environmental pollution. 28-day laboratory pot experiment was carried out applying bioaugmentation using laboratory selected bacterial strains as inoculum, biostimulation with molasses and cabbage leaf extract, and phytoremediation using rye and blue fenugreek to study the effect of these treatments on TNT removal and changes in soil microbial community responsible for contaminant degradation. Chemical analyses revealed significant decreases in TNT concentrations, including reduction of some of the TNT to its amino derivates during the 28-day tests. The combination of bioaugmentation-biostimulation approach coupled with rye cultivation had the most profound effect on TNT degradation. Although plants enhanced the total microbial community abundance, blue fenugreek cultivation did not significantly affect the TNT degradation rate. The results from molecular analyses suggested the survival and elevation of the introduced bacterial strains throughout the experiment. Keywords: TNT, bioaugmentation, biostimulation, phytoremediation, microbial community.

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A life cycle based multi-objective optimization model for the management of computer waste

Cited by 64 publications

References 21 publications

Waste Printed Circuit Boards recycling: an extensive assessment of current status

Waste Printed Circuit Boards recycling: an extensive assessment of current status

Designing a sustainable recovery network for waste from electrical and electronic equipment using a genetic algorithm

Costs Analysis of Municipal Solid Waste Management Scenarios: Iasi – Romania Case Study

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