Manjarres, DianaMabe, LaraOregi, XabatLanda-Torres, Itziar2019Manjarres , D , Mabe , L , Oregi , X & Landa-Torres , I 2019 , ' Two-Stage Multi-Objective Meta-Heuristics for Environmental and Cost-Optimal Energy Refurbishment at District Level ' , Sustainability , vol. 11 , no. 5 , 1495 , pp. 1495 . https://doi.org/10.3390/su110514952692-2924researchoutputwizard: 11556/748Publisher Copyright: © 2019 by the authors.Energy efficiency and environmental performance optimization at the district level are following an upward trend mostly triggered by minimizing the Global Warming Potential (GWP) to 20% by 2020 and 40% by 2030 settled by the European Union (EU) compared with 1990 levels. This paper advances over the state of the art by proposing two novel multi-objective algorithms, named Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Harmony Search (MOHS), aimed at achieving cost-effective energy refurbishment scenarios and allowing at district level the decision-making procedure. This challenge is not trivial since the optimisation process must provide feasible solutions for a simultaneous environmental and economic assessment at district scale taking into consideration highly demanding real-based constraints regarding district and buildings’ specific requirements. Consequently, in this paper, a two-stage optimization methodology is proposed in order to reduce the energy demand and fossil fuel consumption with an affordable investment cost at building level and minimize the total payback time while minimizing the GWP at district level. Aimed at demonstrating the effectiveness of the proposed two-stage multi-objective approaches, this work presents simulation results at two real district case studies in Donostia-San Sebastian (Spain) for which up to a 30% of reduction of GWP at district level is obtained for a Payback Time (PT) of 2–3 years.11725546enginfo:eu-repo/semantics/openAccessjournal article10.3390/su11051495EnergyEnvironmentalGlobal warming potentialDistrict refurbishmentMulti-objectiveOptimizationEnergyEnvironmentalGlobal warming potentialDistrict refurbishmentMulti-objectiveOptimizationGeography, Planning and DevelopmentRenewable Energy, Sustainability and the EnvironmentEnvironmental Science (miscellaneous)Energy Engineering and Power TechnologyManagement, Monitoring, Policy and LawSDG 7 - Affordable and Clean EnergySDG 8 - Decent Work and Economic GrowthSDG 13 - Climate ActionProject IDinfo:eu-repo/grantAgreement/EC/H2020/680676/EU/Optimised Energy Efficient Design Platform for Refurbishment at District Level/OptEEmALinfo:eu-repo/grantAgreement/EC/H2020/680676/EU/Optimised Energy Efficient Design Platform for Refurbishment at District Level/OptEEmALFunding InfoPart of this work has been developed from results obtained during the H2020 “Optimised Energy_x000D_ Efficient Design Platform for Refurbishment at District Level” (OptEEmAL) project, Grant No. 680676.Part of this work has been developed from results obtained during the H2020 “Optimised Energy_x000D_ Efficient Design Platform for Refurbishment at District Level” (OptEEmAL) project, Grant No. 680676.http://www.scopus.com/inward/record.url?scp=85069758471&partnerID=8YFLogxK