Retrofitting of Housing Blocks Minimizing space heating and cost using combinatorial optimization modelling and algorithms

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dc.contributor.authorOnsjö, Kristian
dc.contributor.authorDanielsson, Anton
dc.contributor.departmentChalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)sv
dc.contributor.departmentChalmers University of Technology / Department of Computer Science and Engineering (Chalmers)en
dc.date.accessioned2019-07-03T14:44:57Z
dc.date.available2019-07-03T14:44:57Z
dc.date.issued2018
dc.description.abstractThis report details an approach toward finding Pareto optimal solutions to the problem of retrofitting buildings by modelling it as an integer linear optimization problem. The report discusses some background to its importance, e.g., that many buildings do not currently meet the standards set by the European Union for energy efficiency. A current prognosis shows that these standards will not be met in due time, and as such the DREEAM project aims to improve the work being done on retrofitting buildings. The optimization tool DreeamTool, currently being developed within DREEAM, uses a stochastic algorithm, NSGA-II. In the report it is shown how a method based on integer linear programming with multiple objective functions performs, as opposed to the current method. It is shown that the mathematical model and solution approach finds Pareto optimal solutions in a computation time that is considerably shorter than that used by NSGA-II for finding an approximation of the Pareto front.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/255142
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectData- och informationsvetenskap
dc.subjectComputer and Information Science
dc.titleRetrofitting of Housing Blocks Minimizing space heating and cost using combinatorial optimization modelling and algorithms
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeComplex adaptive systems (MPCAS), MSc
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