Browsing by Keyword "Multi-objective"

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    A Multi-objective Harmony Search Algorithm for Optimal Energy and Environmental Refurbishment at District Level Scale
    (Springer Singapore, 2017) Manjarres, Diana; Mabe, Lara; Oregi, Xabat; Landa-Torres, Itziar; Arrizabalaga, Eneko; Del Ser, Javier; Tecnalia Research & Innovation; IA; PLANIFICACIÓN ENERGÉTICA
    Nowadays municipalities are facing an increasing commitment regarding the energy and environmental performance of cities and districts. The multiple factors that characterize a district scenario, such as: refurbishment strategies’ selection, combination of passive, active and control measures, the surface to be refurbished and the generation systems to be substituted will highly influence the final impacts of the refurbishment solution. In order to answer this increasing demand and consider all above-mentioned district factors, municipalities need optimisation methods supporting the decision making process at district level scale when defining cost-effective refurbishment scenarios. Furthermore, the optimisation process should enable the evaluation of feasible solutions at district scale taking into account that each district and building has specific boundaries and barriers. Considering these needs, this paper presents a multi-objective approach allowing a simultaneous environmental and economic assessment of refurbishment scenarios at district scale. With the aim at demonstrating the effectiveness of the proposed approach, a real scenario of Gros district in the city of Donostia-San Sebastian (North of Spain) is presented. After analysing the baseline scenario in terms of energy performance, environmental and economic impacts, the multi-objective Harmony Search algorithm has been employed to assess the goal of reducing the environmental impacts in terms of Global Warming Potential (GWP) and minimizing the investment cost obtaining the best ranking of economic and environmental refurbishment scenarios for the Gros district.
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    On the design of a novel two-objective harmony search approach for distance- and connectivity-based localization in wireless sensor networks
    (2013-02) Manjarres, Diana; Del Ser, Javier; Gil-Lopez, Sergio; Vecchio, Massimo; Landa-Torres, Itziar; Salcedo-Sanz, Sancho; Lopez-Valcarce, Roberto; IA; Tecnalia Research & Innovation
    In several wireless sensor network applications the availability of accurate nodes' location information is essential to make collected data meaningful. In this context, estimating the positions of all unknown-located nodes of the network based on noisy distance-related measurements (usually referred to as localization) generally embodies a non-convex optimization problem, which is further exacerbated by the fact that the network may not be uniquely localizable, especially when its connectivity degree is not sufficiently high. In order to efficiently tackle this problem, we propose a novel two-objective localization approach based on the combination of the harmony search (HS) algorithm and a local search procedure. Moreover, some connectivity-based geometrical constraints are defined and exploited to limit the areas in which sensor nodes can be located. The proposed method is tested with different network configurations and compared, in terms of normalized localization error and three multi-objective quality indicators, with a state-of-the-art metaheuristic localization scheme based on the Pareto archived evolution strategy (PAES). The results show that the proposed approach achieves considerable accuracies and, in the majority of the scenarios, outperforms PAES.
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    Two-Stage Multi-Objective Meta-Heuristics for Environmental and Cost-Optimal Energy Refurbishment at District Level
    (2019) Manjarres, Diana; Mabe, Lara; Oregi, Xabat; Landa-Torres, Itziar; Tecnalia Research & Innovation; IA; PLANIFICACIÓN ENERGÉTICA
    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.