Therefore, these mathematical programming models for decision support must take explicitly into account, besides multiple and conflicting objective functions, the treatment of the uncertainty associated with the coefficients. In most real-world situations, the coefficients of these models are not exactly known because data is scarce, difficult to obtain or estimate and the system being modeled might be subject to changes. In this manner, the decision-makers benefit from an analytical tool which allows them to assess the environmental impacts, resulting from changes in the level of production of the economic activities that might be sustained by distinct policies. These models allow the decision-makers to incorporate distinct axes of evaluation, namely related with energy sustainable strategies, economic growth, social well-being and environmental concerns. Multiobjective linear programming models based on the linear inter/intra industrial linkages of production are used to study the interactions between the economy, the energy system and the environment. The high external energy dependency and the weight of the fossil fuels on the primary energy consumption imply the country is faced with great challenges regarding the policies it must follow in order to achieve the targets, which have been imposed both for the energy and environmental sectors, without discarding the economic and social issues that are associated to them. The energy sector is particularly relevant in the national context, due to its impacts on the productive system as well as its consequences on the level of employment, internal supply, external relations and the environment.
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