A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Greenhouse Gas Mitigation-Induced Rough-Interval Programming for Municipal Solid Waste Management
A greenhouse gas (GHG) mitigation-induced rough-interval programming model is proposed in this study. Components of GHG emission and environmental pollution control are incorporated into the objective function and a series of relevant constraints. To explicitly examine more complexities existing in many parameters, rough intervals are also communicated into the modeling framework. The proposed model presents satisfactory capabilities in analyzing complicated interrelationships among municipal solid waste (MSW) management, climate-change impact, and environmental pollution control. It can also provide optimal allocation schemes and facilitate decision-makers regulating environmentally sustainable strategies. The developed model is then applied to a case study for demonstrating its applicability. Two representative scenarios (relatively representing two potential management policies that may be implemented in the future years) are considered. The results indicate that the developed model presents advantages in mitigating GHG emissions and the associated climate-change impact. The comparison between the GHG mitigation-induced model with and without rough-interval parameters is also investigated. Completely different solutions of the two models imply the significant impact of dual-uncertain information on the system, which can hardly be addressed through the existing optimization approaches.
Greenhouse Gas Mitigation-Induced Rough-Interval Programming for Municipal Solid Waste Management
A greenhouse gas (GHG) mitigation-induced rough-interval programming model is proposed in this study. Components of GHG emission and environmental pollution control are incorporated into the objective function and a series of relevant constraints. To explicitly examine more complexities existing in many parameters, rough intervals are also communicated into the modeling framework. The proposed model presents satisfactory capabilities in analyzing complicated interrelationships among municipal solid waste (MSW) management, climate-change impact, and environmental pollution control. It can also provide optimal allocation schemes and facilitate decision-makers regulating environmentally sustainable strategies. The developed model is then applied to a case study for demonstrating its applicability. Two representative scenarios (relatively representing two potential management policies that may be implemented in the future years) are considered. The results indicate that the developed model presents advantages in mitigating GHG emissions and the associated climate-change impact. The comparison between the GHG mitigation-induced model with and without rough-interval parameters is also investigated. Completely different solutions of the two models imply the significant impact of dual-uncertain information on the system, which can hardly be addressed through the existing optimization approaches.
Greenhouse Gas Mitigation-Induced Rough-Interval Programming for Municipal Solid Waste Management
Lu, Hongwei (author) / Huang, Guohe (author) / Liu, Zhenfang (author) / He, Li (author)
Journal of the Air & Waste Management Association ; 58 ; 1546-1559
2008-12-01
14 pages
Article (Journal)
Electronic Resource
Unknown
Greenhouse Gas Emission Mitigation Relevant to Changes in Municipal Solid Waste Management System
| Taylor & Francis Verlag | 2010
FSILP: Fuzzy-stochastic-interval linear programming for supporting municipal solid waste management
| Online Contents | 2011
An Interval Mixed-Integer Semi-Infinite Programming Method for Municipal Solid Waste Management
| Taylor & Francis Verlag | 2009
| Taylor & Francis Verlag | 2006