Author
Luis C. Dias
Other affiliations: Paris Dauphine University, Massachusetts Institute of Technology
Bio: Luis C. Dias is an academic researcher from University of Coimbra. The author has contributed to research in topics: ELECTRE & Decision support system. The author has an hindex of 32, co-authored 141 publications receiving 4282 citations. Previous affiliations of Luis C. Dias include Paris Dauphine University & Massachusetts Institute of Technology.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a multi-objective optimization model is presented to assist stakeholders in the definition of intervention measures aimed at minimizing the energy use in the building in a cost effective manner, while satisfying the occupant needs and requirements.
410 citations
TL;DR: In this paper, a multi-objective optimization model using genetic algorithm (GA) and artificial neural network (ANN) is presented to quantitatively assess technology choices in a building retrofit project.
345 citations
TL;DR: A new interactive approach is proposed, where the insight obtained during robustness analyses guides the DMs during the elicitation phase, by integrating two approaches developed independently to deal with the case where the decision makers are unsure of which values should each parameter take.
249 citations
TL;DR: In this paper, a simulation-based multi-objective optimization scheme (a combination of TRNSYS, GenOpt and a Tchebycheff optimization technique developed in MATLAB) is employed to optimize the retrofit cost, energy savings and thermal comfort of a residential building.
237 citations
TL;DR: This work addresses the problem of identifying subsets of constraints which, when removed, lead to a consistent system and presents two algorithms to identify such subsets using mixed integer linear programming and linear programming.
187 citations
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6,977 citations
TL;DR: In this article, the authors reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation.
Abstract: Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making for sustainable energy because of the multi-dimensionality of the sustainability goal and the complexity of socio-economic and biophysical systems. This article reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation. The criteria of energy supply systems are summarized from technical, economic, environmental and social aspects. The weighting methods of criteria are classified into three categories: subjective weighting, objective weighting and combination weighting methods. Several methods based on weighted sum, priority setting, outranking, fuzzy set methodology and their combinations are employed for energy decision-making. It is observed that the investment cost locates the first place in all evaluation criteria and CO2 emission follows closely because of more focuses on environment protection, equal criteria weights are still the most popular weighting method, analytical hierarchy process is the most popular comprehensive MCDA method, and the aggregation methods are helpful to get the rational result in sustainable energy decision-making.
1,868 citations
TL;DR: A review of the current state of the art in computational optimization methods applied to renewable and sustainable energy can be found in this article, which offers a clear vision of the latest research advances in this field.
Abstract: Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.
1,394 citations
TL;DR: A classification scheme and a comprehensive literature review are presented in order to uncover, classify, and interpret the current research on PROMETHEE methodologies and applications.
1,325 citations
TL;DR: In this paper, a Soft Systems Methodology in Action is presented, with a focus on the soft systems methodology in action, and a discussion of its application in soft systems.
Abstract: (1991). Soft Systems Methodology in Action. European Journal of Information Systems: Vol. 1, No. 3, pp. 215-216.
1,011 citations