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dc.contributor.advisorBiswajit Sarkar-
dc.contributor.authorMuhammad Salman Habib-
dc.date.accessioned2018-04-18T06:06:57Z-
dc.date.available2018-04-18T06:06:57Z-
dc.date.issued2018-02-
dc.identifier.urihttp://www.dcollection.net/handler/hanyang/000000104795en_US
dc.identifier.urihttp://repository.hanyang.ac.kr/handle/20.500.11754/68161-
dc.description.abstractSince last few decades, disasters occur in an increasing frequency with devastating impact globally. These disasters generate thousands of tons of waste, which in short-term impede evacuation and relief distribution operation while in the long-run they hinder the social and economic recovery of some affected areas. A significant portion of the cost associated with disaster recovery phase is spent on managing disaster debris. Increasing cost of debris processing and political willingness to achieve sustainability targets have brought the debris management operation to the greater importance than others. Currently, disaster management policies, particularly in developing countries are reactive in nature with the aim to bring the community back to routine life as early as possible ignoring the long-term goals for sustainability. However, increased resilience against future disasters can only be obtained by achieving long-term goals for economic, environmental, and social sustainability. In this context, this dissertation presents a two-stage framework for sustainable disaster debris management by merging the debris management operations with sustainability framework. The first stage of the proposed debris management framework deals with the immediate environmental and health threats in disaster-affected regions posed by the disaster debris. This stage consists of following tasks: debris estimation, selection of temporary disaster debris management site (TDDMS), and debris allocation to selected TDDMS. For debris estimation, United States Army Corps of Engineers (USACE) debris estimation model is used, while for TDDMS selection task a combination of multi-criteria decision-making methodologies-
dc.description.abstractanalytical network process (ANP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) are employed. Finally, to allocate debris from affected regions to the selected TDDMS a debris allocation optimization model using fuzzy possibilistic programming approach is developed. The second stage of the debris management framework considers strategic planning and actions to address permanent impacts of debris processing techniques on the community from economic, environment, and social sustainability perspective. In this direction, this dissertation proposes an optimization model for debris processing supply chain considering an economic aspect through total debris processing cost minimization, environmental aspect by greenhouse gas emissions minimization from debris processing, and social aspect by job opportunities maximization from debris processing. As the parameters of the proposed model are tainted with uncertainty due to the uncertain environment of disaster, robust possibilistic programming (RPP) based solution methodology is employed to obtain preferred compromise solutions for the proposed optimization model. Several variants of RPP are developed and their pros and cons, and the situations of each possible variant are discussed. Furthermore, to convert the multi-objective model into a single objective model, a modified version of weighted Werners method is introduced. For illustrating the utilization of the proposed debris management framework, numerical examples for both stages are provided. Numerical outcomes prove that the proposed framework results in a sustainable debris management system for disasters.-
dc.publisher한양대학교-
dc.titleRobust Optimization for Post-Disaster Debris Management in Humanitarian Supply Chain: a Sustainable Recovery Approach-
dc.typeTheses-
dc.contributor.googleauthor하비브무하마드살만-
dc.sector.campusS-
dc.sector.daehak대학원-
dc.sector.department산업경영공학과-
dc.description.degreeDoctor-
Appears in Collections:
GRADUATE SCHOOL[S](대학원) > INDUSTRIAL MANAGEMENT ENGINEERING(산업경영공학과) > Theses (Ph.D.)
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