Carla Henriques

This paper is aimed at presenting a multiobjective interval portfolio framework which considers investment decisions under different risk assumptions. New surrogate problems are obtained for the mean-absolute deviation risk measure based on the concept of necessary subtraction between interval numbers. A proposal for obtaining the efficient portfolio solutions is also suggested, which allows accounting for three types of investment strategies. Indices of robustness have also been computed, which allow assessing the assets which are more often selected irrespective of the investment strategy followed, and regardless of the business cycle contemplated. Results illustrate the trade-off between risk and return, being also consistent with the type of strategy followed by the investor. Overall, we were able to conclude that less prone to risk investors might find the formulation based on the mean-absolute necessary deviation more appealing since it allows reaching, in general, lower volatility of returns.

Input-output (IO) analysis is a useful tool for the assessment of the inter-relations between different economic activities. Additionally, it can be combined with bottom-up data, i.e. energy-efficient technology-specific data, costs and cost structures, allowing to estimate the Economic-Energy-Environmental (E3) impacts intertwined with the investment on this type of technologies within a comprehensive and consistent framework. With the foregoing in mind, an adjusted Economic IO Lifecycle Assessment (EIO LCA) modelling framework has been built with real data based on the World IO Database to appraise the impacts of fostering the investment in nine distinct energy-efficient appliances typically used in India’s residential sector. A large platform of real data for India’s residential sector has also been gathered considering different sources of information, namely the number of operating days, the lifetime and the investment cost of each energy-efficient appliance evaluated. Finally, it was possible to compute the net E3 impacts obtainable with the use of energy-efficient technologies when contrasted with business-as-usual appliances in India. An economic analysis was also performed for the technologies under analysis specifically addressing the net present value, the savings to investment ratio and the cost of conserved energy. Finally, a correlation study of all the indicators obtained has been conducted in order to study the trade-offs involved in our multiperspective assessment.

Energy planning in many developing Asian countries has neglected the structure of energy demand and how it is likely to evolve as development takes its path. The limited availability of energy consumption data makes it very difficult to assess the energy savings potential at end-use level. Energy planning requires the formulation of a proper modelling framework that supports the definition of energy policies. From the different approaches available, Input – Output (I-O) models are particularly useful, since they allow considering different impacts that can be consistent with different energy policy options. This paper proposes a novel I-O modelling framework by introducing a bottom-up approach into an I-O model which is combined with technical data for the holistic assessment of energy efficient technologies in the residential sector, which can assist energy decision-makers of India on the appraisal of the future impacts of the current national energy saving targets. A large size platform of real data has also been gathered considering different data sources, namely the household building stock characterization, the number of operating days according to the climatic regions of India, the lifetime and the investment cost of each equipment. Finally, the main results are discussed and future research opportunities are identified.

Traditionally, energy planning in developing Asian countries has neglected the structure of energy demand and how it is likely to evolve as development takes its path. Additionally, the lack of concern with the conservation of energy and the limited availability of energy consumption data has made it very difficult to assess in a reasonable manner the potential for energy savings in the major energy end-use sectors. Energy planning is a challenging endeavour, thus requiring the formulation of a proper modelling framework that supports decision-makers with the definition of energy policies without compromising future energy needs. From the different approaches available in the scientific literature, Input – Output (I-O) models are particularly useful, since they allow considering different impacts (e.g.  economic, social and environmental) that can be consistent with different energy policy options. This paper is aimed at designing an I-O modelling framework for assessing several energy efficient technologies in the residential sector, which assists planners and energy decision-makers of India on the appraisal of the future impacts of the current national energy saving targets and thus help to shape future energy plans in this country. An adjusted I-O model has been built with real data based on the World I-O Database (National I-O tables, Socio Economic Accounts and Environmental Accounts) to assess the economic, energy, environmental and social impacts of the investment in nine distinct energy efficient appliances. A large size platform of real data has also been gathered considering different data sources, namely the household building stock characterization, the number of operating days according to the climatic regions of India, the lifetime and the investment cost of each energy efficient equipment considered, the energy savings obtained with energy efficient against conventional technologies, the electricity generation mix in India and the corresponding generation cost. Finally, the main results of this assessment are discussed and future research opportunities are identified.

A multiobjective optimization model with interval coefficients based on portfolio theory has been formulated to support public bodies with the selection of the industrial lighting efficient portfolios to be subsidized. The objective functions considered are the maximization of the return measured as the savings to investment ratio per unit invested and the minimization of risk as the maximization of the minimum deviation of energy savings of the portfolio throughout its lifetime from the expected energy embodied (energy input) in its production. Constraints regarding the maximal capital allocated to the various lighting technologies are also considered under the imposition of a certain energy payback time. Finally, an approach for obtaining the efficient portfolio lighting technologies has also been proposed which allows exploring three types of investment strategies, i.e., a conservative strategy, an aggressive strategy and a combined strategy for obtaining these solutions.

Addressing the impacts of energy efficient lighting systems in the industrial sector from a multidimensional perspective requires the formulation of a proper modelling framework. Input-Output (IO) models can be particularly suitable, since they can be adjusted to embed economic, social and environmental impacts that can be consistent with different energy policy recommendations. This paper is aimed at presenting an IO modelling framework which allows for the appraisal of economic, energy and environmental (E3) impacts of several energy efficient lighting systems in the Portuguese industrial sector, grasping their trade-offs by means of a multiobjective integer programming (MOIP) problem.

The conventional transportation problem usually involves the transportation of goods from several supply points to different demand points and considers the minimization of the total transportation costs. The transportation problem is a special case of linear programming models, following a particular mathematical structure, which has a wide range of potential practical applications, namely in logistic systems, manpower planning, personnel allocation, inventory control, production planning and location of new facilities. However, in reality,the transportation problem usually involves multiple, conflicting, and incommensurable objective functions, being called the multiobjective transportation problem. Several methods have been developed for solving this sort of problems with the assumption of precise information regarding sources, destinations and crisp coefficients for the objective function coefficients. Nevertheless, when dealing with real-life transportation problems, these circumstances may not be verified, since the transportation costs may vary as well as supply and demand requirements. Therefore, different approaches for dealing with inexact coefficients in transportation problems have been proposed in scientific literature, namely with the help of fuzzy and interval programming techniques. This paper is aimed at providing a short critical review of some interval programming techniques for solving this particular type of problems.

Our paper aims at contrasting the use of two alternative approaches usually used for the assessment of the environmental implications of electricity generation: Economic Input-Output Life-Cycle Assessment (EIO-LCA) and Process-based Life Cycle Assessment (P-LCA). EIO-LCA is a top-down approach intertwined with the environmental satellite accounts provided by the national statistical office. The EIO-LCA analysis uses economic input-output (IO) tables and industrial sector level environmental/energy data allowing broad impact coverage of all sectors directly and indirectly involved with electricity generation. P-LCA is a bottom-up approach, in which a detailed modelling of the various electricity technologies is performed following a life cycle perspective that entailing a higher level of detail. The paper provides a brief overview of both methodologies and corresponding assumptions, followed by the discussion of the major drawbacks and strengths inherent to their application to the electricity sector.

Energy efficient lighting reduces the demand for electricity and its corresponding environmental impacts. In fact, lighting can represent a significant portion of energy and electricity consumption in public facilities. On the other hand, energy is the largest cost in owning and operating a typical lighting system. Finally, besides energy savings, energy efficient lighting often represents additional cooling and operation and maintenance savings. This paper is aimed at presenting the appraisal of several energy efficiency measures for the interior lighting system of distinct Portuguese municipal facilities. Besides the characterization of the currently available lighting systems, the study presents the technical-economic analysis of the efficiency measures selected for each space analysed, by taking into account the space´s characteristics and both electrical and photometric characteristics of the luminaires, ensuring its longevity as well as the suitable light levels required.

This study is aimed at identifying and assessing distinct energy efficiency measures that can be implemented in residential buildings, taking into account different areas of intervention and multiple aspects of evaluation (technical, economic, environmental and social). The assessment of the different identified measures will be performed through the Electre Tri method which is devoted to the sorting problem. The results obtained allow supporting policy decision-makers with the selection of measures which have the highest implementation potential and that may be elected for public support and / or public funding.

Energy sustainable strategies in Europe advocate increasing the share of electricity generated from renewable energy sources (RES-E) in response to the need of reducing Green House Gas (GHG) emissions. RES-E production is considered to have a prominent role in the crusade against climate change and in Europe’s energy security. Renewable energy technology (RET) deployment is also sought for promoting a large number of jobs. Nevertheless, the exact number of jobs created is presented with large discrepancies across recent studies. The use of different methodologies but also the consideration of different assumptions even when the same methodology is applied has implications on the variability of employment estimates. This paper is aimed at providing a clearer understanding of what are the implications of government support for RES-E on jobs, and to see if current claims over employment benefits are too optimistic or even pessimistic in light of these findings. Taking Portugal as a case study, this paper conveys an assessment of the impact of renewable energy targets for electricity generation on employment for the years 2008 to 2020. The analysis is conducted by means of the Input-Output (IO) approach (quantity and price models) and considering the different life cycle stages of RES-E and conventional electricity (CE) power plants.

The energy sector has been a fertile ground for the application of operational research (OR) models and methods (Antunes and Martins, 2003). Even though different concerns have been present in OR models to assess the merit of potential solutions for a broad range of problems arising in the energy sector, the use of multi-objective optimization (MOO) and multi-criteria analysis (MCA) approaches is more recent, dating back from mid-late 1970s. The need to consider explicitly multiple uses of water resource systems or environmental aspects in energy planning provided the main motivation for the use of MOO and MCA models and methods with
a special evidence in scientific literature since the 1980s. The increasing need to account for sustainability issues, which is inherently a multi-criteria concept, in planning and operational decisions, the changes in the organization of energy markets, the conflicting views of several stakeholders, the prevalent uncertainty associated with energy models, have made MOO and MCA approaches indispensable to deal with complex and challenging problems in the energy sector. This paper aims at providing an overview of MOO and MCA models and methods in a vast range of energy problems, namely in the electricity sector, which updates and extends the one in Diakoulaki et al. (2005). Broadly, models and methods dealing with multi-objective mathematical programming and a-priori explicitly known discrete alternatives are distinguished and some of the main types of problems are stated. The main conclusion is that MOO and MCA approaches are essential for a thorough analysis of energy problems at different decision levels, from strategic to operational, and with different timeframes.

In response to the need of reducing Green House Gas (GHG) emissions, energy strategies in Europe advocate increasing the share of electricity generated from renewable energy sources (RES-E). RES-E production is considered to be a priority in the crusade against climate change, with a crucial role in Europe’s energy security. Several studies even suggest that renewable energy technology (RET) deployment will also be responsible for the creation of a large number of jobs. Nevertheless, the exact number of jobs created varies enormously across recent studies. Employment estimates may vary not only with the use of different methodologies but also with the consideration of different assumptions even when the same methodology is applied. The aim of this paper is to provide a clearer understanding of what are the implications of government support for
RES-E on jobs, and to see if current claims over employment benefits are too optimistic or even pessimistic in light of these findings. Taking Portugal as a case study, this paper conveys an assessment of the impact of renewable energy targets for electricity generation on employment for the year 2020. The analysis is conducted by means of the Input-Output (IO) approach (quantity and price models) and considering the different life cycle stages of RES-E and conventional energy (CE) power plants.

Employment effects of electricity production from renewable energy in Portugal – an IO LCA approach,. Available from: https://www.researchgate.net/publication/276335606_Employment_effects_of_electricity_production_from_renewable_energy_in_Portugal__an_IO_LCA_approach [accessed May 21, 2015].

A multi-objective linear programming (MOLP) model based on a hybrid Input-Output (IO) framework is presented. This model aims at assessing the trade-offs between economic, energy, environmental (E3) and social objectives in the Brazilian economic system. This combination of multiobjective models with Input-Output Analysis (IOA) plays a supplementary role in understanding the interactions between the economic and energy systems, and the corresponding impacts on the environment, offering a consistent framework for assessing the effects of distinct policies on these systems. Firstly, the System of National Accounts (SNA) is reorganized to include the National Energy Balance, creating a hybrid IO framework that is extended to assess Greenhouse Gas (GHG) emissions and the employment level. The objective functions considered are the maximization of GDP and employment levels, as well as the minimization of energy consumption and GHG emissions. An interactive method enabling a progressive and selective search of non-dominated solutions with distinct characteristics and underlying trade-offs is utilized. Illustrative results indicate that the maximization of GDP and the employment levels lead to an increase of both energy consumption and GHG emissions, while the minimization of either GHG emissions or energy consumption cause negative impacts on GDP and employment.

This paper develops a bottom-up approach in the scope of a multi-objective linear programming model (MOLP) based on Input-Output (I-O) analysis to account for investment options aimed at improving the thermal properties of building envelope (e.g., the insulation of external walls and roof, and the replacement of window frames and window glazing). This methodological framework aims at assessing the trade-offs between the overall employment, GDP and energy savings associated with the building sector (residential, private services and public services). Distinct impacts, namely on direct and indirect employment generation, environment emissions), energy security supply (energy imports and renewable energy production) and other relevant economic indicators are also analysed. Different sets of input parameters for the economic context and the environmental impacts have been defined as interval coefficients to account for uncertainty. Robust solutions are then obtained by considering the minimisation of the worst possible deviation of the interval objective functions to the corresponding interval ideal solutions.

In response to the need of reducing CO2 emissions, the European Union has set itself ambitious targets to increase the share of electricity generated from renewable energy sources (RES-E). Therefore, the promotion of the deployment of renewable energy technologies has come to form a crucial part of governments’ strategies to prevent climate change. Although it is difficult to refute the claim that increasing the use of RES-E will help to prevent global warming, along with adding to Europe’s energy security, policy-makers and ‘green growth’ advocates further argue that it will lead to the creation of a large number of jobs. However, the exact number of jobs quoted by current studies varies enormously with a tendency for member states to base policy decisions on employment estimates that are arguably too optimistic. Taking the UK as a case study, this paper provides an assessment of the impact that renewable energy targets for electricity generation will have on employment. The job creating potential of each RES-E will be made available through the use of Input-Output employment multipliers with projections for the year 2020. The analysis indicates that the number of jobs associated with RES-E is expected to be less than anticipated by the UK government. Thus with employment benefits smaller than anticipated, and as a consequence less able to offset any negative employment effects that are likely to transpire from the move to a low carbon economy, it is argued that current policy measures do not adequately
protect or prepare the workers for this transition.

"""Interval programming techniques are a valuable approach for tackling uncertainty in mathematical programming models, because they only require the knowledge of the feasible range of variation of the model coefficients. Nevertheless, the use of these techniques has some limitations, namely when the number of decision variables with interval coefficients is high since
the number of objective functions at stake in the sub-problem for testing the (weak) efficiency of each non-basic variable may be easily out of an acceptable computational effort. A similar problem may arise with the number of sub-problems for testing the multiparametric optimality of each solution obtained (that is, to check whether the solution is possibly optimal or not) and the multiparametric optimality of each edge by using the all emanating edges algorithm. An alternative algorithm is suggested that allows obtaining all possibly optimal solutions, which fulfill the formal criteria of optimality in a feasible bounded region."""

Monitoring the potential impact on employment creation of renewable energy (RE) and energy efficiency (EE) sectors is particularly important, namely in the current economic conjuncture where unemployment is raising in a fast pace. In this context, a tentative survey was conducted and sent to more than 500 entities operating in these industries, to assess the direct job creation impact of renewable Energy technologies (RET) deployment and EE initiatives as well as to determine the types of jobs eventually created, and the short to mid-term quantitative and qualitative employment outlook. Although the rate of responses to the survey does not allow making any statistical inferences, preliminary results might give an impression that employment in these sectors is stagnating.

Portugal is in line with the European Union (EU) impetus towards a cleaner, more efficient, sustainable energy system that delivers direct benefits, such as less investment needs and lower maintenance cost, as well as a positive environmental impact through the reduction of fossil fuels use to produce energy. Apart from these direct benefits of embracing energy efficiency (EE), the indirect benefit of employment creation has also been emphasized in EU and national strategies as an advantage stemming from the promotion and application of renewable energy (RE) and EE policies. Job creation impacts from RE and EE deployment in the present Portuguese context are challenging to dissociate, because the broad-spectrum of current Portuguese companies are operating in both market segments and do not provide disaggregated information.
In spite of the acknowledged potential of a sustainable energy system to create jobs, the adequate methodologies are yet to be developed. This gap in job impact measurement methodologies is elaborated both at EU level (EC, 2012) and also in the Portuguese National Energy Efficiency Action Plan (NEEAP) (PT, 2013).
The development of this study to quantify the impacts of sustainable energy in Portugal was driven by the national challenge of reduction of current unemployment rates alongside with the potential contribution of EE and RE to support this decrease in the high unemployment rates registered since 2007. The results presented through this paper focus on the EE impacts results (Pereira, 2014), further details on RE are presented in Šahović (2014). Complementary studies and additional results can be found in (Silva et al, 2013) and in (Oliveira et al, 2013).

The purpose of this paper is to provide an integrated methodology which follows different stages and connects top-down and bottom-up approaches, such as Input-Output (I-O) multipliers, traditional capital budgeting assessment tools and Multicriteria Decision Analysis to facilitate the combined evaluation of different energy efficiency renovation projects. In the current context of environmental concerns along with energy efficiency targets, the case study presented focuses on the global and local impact assessment of renovation projects on buildings from the residential, private services and public services sector, built within
the range of 1946 to 1990.

Energy efficiency plays a significant role in increasing the security of energy supply and mitigating climate change. Although this role is indubitable, there is an ongoing discussion about the employment impacts of promoting energy efficiency measures, in particular of building retrofit investments. The purpose of this paper is to provide an estimation of the number of net jobs associated with the most common retrofit investment options in the building stock of Portugal. The examined investment options aim at improving the thermal properties of the building envelope and include the insulation of external walls and roof and the substitution of windows frames and single glazed windows. The implementation of a methodological framework for the assessment of employment benefits is based on Input-Output (I-O) analysis, providing consistent estimates for depicting the significant contribution of energy saving measures in the building sector (residential, private services and public services) in net employment generation.

MCDA methods become increasingly popular in energy decision-making due to their capability to deal with complex decision processes, in face of multiple and conflicting evaluation criteria (of technical, economic, environmental and social nature), different stakeholders with different views and preferences, several sources of uncertainty and distinct time frames. Literature reviews with specific focuses on the use of MCDA in energy problems have been reported. Hobbs and Meier (2000) provide a wide review of MCDM methods and energy-environment applications. Greening and Bernow (2004) describe a modeling framework incorporating developments in integrated assessment of energy and environmental issues, and suggest a strategy for developing a set of coordinated policies from varying levels of information about policy attributes and DM’s preferences. Pohekar and Ramachandran (2004) review the application of various MCDM methods in the framework of sustainable energy planning. Løken (2007) provide an overview of some of the most relevant MCDA methods proposed in the literature. Mirakyan and Guio (2013) present a review of methods and tools for integrated energy planning in cities and territories, concluding that the purpose of MCDA methodologies is not just required to define the “right” energy plan but rather to support the understanding of the multi-criteria complex situation that supports interactive planning and learning, helping people to systematically consider, articulate and apply value judgments.
The poblems most often dealt with with MCDA approaches are:
- Comparison of power generation technologies, involving the appraisal of available primary energy sources and technological options, considering conventional technologies and/or renewable energy technologies.
- Formulation and development of energy plans and policies, involving the choices faced by energy planners at the national, regional or local level seeking to identify the most desired one among alternative scenarios, taking into account the public debate on energy policy, energy conservation strategies and energy resource allocation issues.
- Selection of energy projects, namely concerning renewable energy investments for electricity generation.
- Location decisions, namely focussing on the siting of new wind farms and hydro and thermal power plants, also complemented with choices regarding operational parameters.
- Energy efficiency studies, mainly devoted to the evaluation of energy efficiency measures and programs either in technology replacement or building refurbishment.

In the last years Portugal has been at the forefront in the deployment of electricity from renewable energy sources (RES-E). The Portuguese national energy strategy 2020 (NES 2020) aims to reinforce Portugal’s leadership in sustainable energy and to attain the ambitious goals set in the government programme, namely consolidating the renewable energies cluster in Portugal, which will represent approximately by 2020 more than three times the 35,000 jobs estimated in 2010 and further developing the industrial cluster related with energy efficiency, creating 21,000 new jobs.

The main purpose of this paper is to perform a prospective study and to discuss the various factors that influence the appraisal of sustainable systems integrating environmental, social and economic dimensions, mainly focusing on the RES-E jobs case by means of a multiobjective Input–Output model, based on current data availability.

"Following the EU trends, energy has been at the top of national agenda in Portugal and the country has been quickly emerging as a “green” trendsetter due to its determination to reduce its dependence on imported fossil fuels by channelling its wind, solar, and hydropower resources - even though such clean energy transitions have come at substantial financial costs.
In the context of the so-called Climate Change and Energy package for 2020 by the European Commission, Portugal has to meet a target of 31% regarding the share of renewable sources on gross final energy consumption, including 10% in transportation, to meet the targets imposed on greenhouse gas emissions, energy efficiency and use of renewable energy. The National Renewable Energy Action Plan (NREAP), prepared and written on the basis of the Commission Decision of 30th of June 2009, which provides for a template for national renewable energy action plans in the Directive 2009/28/EC, includes measures for achieving renewable energy targets and an overview of all policies and measures to promote the use of energy from renewable sources. In this context, one of the most promising renewable energy technologies is photovoltaic (PV) technology (i.e. devices that transform solar energy into electricity). Photovoltaic is a truly elegant means of producing electricity on site, directly from the sun, without concern for energy supply or environmental harm. These solid-state devices simply make electricity out of sunlight, silently with no maintenance, no pollution, and no depletion of materials. The purpose of this paper is to provide an integrated analysis of photovoltaic systems, based on outputs and results from energy/environmental analysis, and other tools such as financial appraisal will also be performed in order to assess how these systems perform on the building sector level or when compared to other energy technologies."

"Although sustainable development has been accepted as an environmental issue, mainly focusing on the integration of environmental and economic dimensions, the social dimension has also been generally recognized as an equal part of sustainable development. In this context, the need for further integration of economic and social policies requires improved integration of social and economic statistics.
In the last years Portugal became a world leader in the deployment of renewable energies. The Portuguese national energy strategy 2020 (NES 2020) aims to reinforce Portugal’s leadership in sustainable energy and to attain the ambitious goals set in the government programme, namely consolidating the renewable energies cluster in Portugal, which will represent by 2020 a Gross Added Value of 3800 million Euros and 100000 new jobs beyond the current 35000 jobs and further developing the industrial cluster related with energy efficiency, creating 21000 new jobs.
The main purpose of this paper is to perform a prospective study and to discuss the various factors that influence the analysis of sustainable development and its impact on a particular and critical social dimension: the employment, mainly focusing on the renewable energy jobs case by means of a multiobjective Input-Output model, based on current data availability."

"Renewable energy is playing an increasing role in energy mixes around the world, including Europe, which is aiming for a target of 20% renewable energy by 2020. Portugal is at the forefront of the European intention, with a 31% target. The advantages of the application of renewable energy policies are widely accepted to include a decrease in greenhouse gas emissions and an improvement in energy security. In many cases job creation is also touted as a benefit but this claim stands on an uncertain footing.
Amongst the variety of methodologies, analytical studies using extensive surveys seem to be more appropriate for regional studies while linear simulations, either in the form of input-output (I-O) analysis or, in recent years, social accounting matrix (SAM) multiplier analysis appear to better suit national and international studies. This paper offers an assessment of the impact of Portuguese ‘green’ energy policies on the employment level departing from a system of symmetric input-output tables recently built for Portugal by the Department of Foresight and Planning.
"

Portugal is a member-state of the European Union (EU), with a GDP at market and current prices of 171 858, 5 *106 € in 2011, a small peripheral economy when compared to the EU-27 average GDP of 468 534, 1 *106 € in 2011 [1]. Concurrently, it is one of the highest external energy dependent European countries (83.1% in 2008), contrasting with the EU-27 average energy dependency (53.8%), mainly because of Portugal’s lack of primary energy sources [1]. Nevertheless, Portugal has been in the forefront of energy policy making, having to comply with several ambitious targets. These overall goals may be seen as a consequence of the set of European Directives in the energy field (already transposed into national law), which have their grounds on three broad pillars: competitiveness, security of supply and sustainability. In this chapter we aim at systematizing and revisiting the energy liberalization process in Portugal, covering the evolution of the regulatory ruling, the tariffs setting, the role of the Iberian Electricity Market and the diversity of the most up to date legislative framework, with a special focus on the renewables field, in the context of an economic recession period. Finally, it will be our purpose to shed some light on the legacy costs which are to be imposed on the next generation of consumers and citizens in a near future, due to the utmost goal of building a true competitive energy market.

The global financial crisis has brought severe impacts on the Portuguese economy. In this context, the Portuguese government has recently adopted harsh measures that will have deep impacts on peoples' lives. This paper discusses the influence of these measures on economic growth, social well-being, energy consumption as well as its impacts on the environment using a multi-objective linear programming model based on input–output analysis. Uncertainty is captured taking into account different model coefficient settings by means of interval programming tools.

Portugal is faced with important challenges concerning the definition of policies to achieve energy and environmental targets, taking also into account the economic and social issues. A multi-sectoral economy–energy–environment model has been developed to perform a prospective analysis of the changes in the economic structure and the energy system, as well as to assess the corresponding environmental impacts, providing decision support in policy making. This model is a multi-objective linear programming model that allows for the explicit consideration of distinct axes of evaluation, generally conflicting and non-commensurate, of the merit of distinct policies. The policy recommendations obtained are subject to the inherent uncertainty associated with the model coefficients and, therefore, they may not be robust in face of changes of the input data. The specification of less energy or carbon-intensive technologies is done by considering pollutant/energy coefficients defined as intervals. This analysis is crucial for understanding the role of technology in carbon mitigation efforts and other energy system planning settings, allowing to explore the effects of distinct policies on the total system costs, the fuel and technology mix, and the levels of greenhouse gases and other emissions.

"The Global Financial Crisis has brought severe impacts on the Portuguese economy. In this context, the Portuguese government has recently adopted harsh measures that will have deep impacts on peoples’ lives. This paper discusses the influence of these measures on economic growth, social well-being, energy consumption as well as its impacts on the environment
through the use of a multi-objective linear programming model based on input–output analysis, taking into account different coefficient settings by means of interval programming tools. "

"A sustainability model offers the framework for differentiated analyses, which go beyond economic factors and include environmental and social effects of different policy measures.
These models enable gaining knowledge about possible impacts of different policy measures on economic, social and environmental aspects. In particular, multiple objective linear programming models based on the linear inter/intra industrial linkages of production (that is input-output analysis) can be used to study the interactions between the four main pillars of sustainable development: economy, energy, social and environmental concerns. These models allow assessing the environmental and social impacts resulting from changes in the level of the economic activities associated with distinct policies, through the explicit consideration of distinct axes of evaluation of the merits of different policies that are modeled as objective functions: Maximization of Gross Domestic Product as proxy for assessing the economic
growth, maximization of the level of employment as a measure of social well-being, minimization of the energy imports as a way of minimizing the energy dependency of the country, and minimization of GHG emissions in order to account for the environmental impacts of the economic activities. In this context, the input-output framework provides a tool for determining the number of jobs created, but as the body of literature concerning sustainability and employment grows it has become increasingly obvious that there is no
consensus on how best to measure job creation, especially for particular technologies. This paper presents a discussion of the various factors that influence the analysis of sustainable development and its impact on the employment level."

A multi-sectoral economy-energy-environment model is proposed to perform a prospective analysis of the changes in the economic structure and the energy system resulting from different policies, as well as to assess the corresponding environmental impacts, providing decision support in policy making. The model is a top-down macro-economic multi-objective model, which allows taking into account the energy carriers associated with primary supplies, conversion and transformation processes. The demand for energy services is disaggregated by economic sectors and may be disaggregated by specific functions within a sector. The model allows to explore the effects of new less energy-intensive or carbon-intensive technologies on the total system costs, changes in fuel and technology mix, and the levels of greenhouse gases and other emissions. This is done in the model framework by considering pollutant/energy coefficients defined as intervals, which capture the uncertainty associated with new processes and/or technologies. This type of analysis is of outstanding importance for understanding the role of technology in carbon mitigation efforts and other energy system planning studies at a macro level.

"Multiple objective programming models allow for the explicit consideration
of distinct axes of evaluation, generally conflicting and non-commensurable, of the merit of solutions. In particular, multiple objective linear programming (MOLP) models based on the linear inter/intra industrial linkages of production can be used to study the interactions between the economy, the energy system and the environment. These models allow assessing the environmental impacts resulting from changes in the level of the economic activities sustained by distinct policies. However, the uncertainty associated with the model coefficients, namely those derived from Input-Output
(I-O) analysis, may lead to conclusions that are not robust regarding the changes of the input data. In this context a MOLP model based on I-O analysis with interval coefficients is proposed, which allows assessing the impacts of distinct policies on the economy, the energy system and the environment, based on the levels of activity of the economic sectors."

Mathematical programming models for decision support must explicitly take account of the treatment of the uncertainty associated with the model coefficients along with multiple and conflicting objective functions. Interval programming just assumes that information about the variation range of some (or all) of the coefficients is available. In this paper, we propose an interactive approach for multiple objective linear programming problems with interval coefficients that deals with the uncertainty in all the coefficients of the model. The presented procedures provide a global view of the solutions in the best and worst case coefficient scenarios and allow performing the search for new solutions according to the achievement rates of the objective functions regarding both the upper and lower bounds. The main goal is to find solutions associated with the interval objective function values that are closer to their corresponding interval ideal solutions. It is also possible to find solutions with non-dominance relations regarding the achievement rates of the upper and lower bounds of the objective functions considering interval coefficients in the whole model.

In most real-world situations, the coefficients of decision support models are not exactly known. In this context, it is convenient to consider an extension of traditional mathematical programming models incorporating their intrinsic uncertainty, without assuming the exactness of the model coefficients. Interval programming is one of the tools to tackle uncertainty in mathematical programming models. Moreover, most real-world problems inherently impose the need to consider multiple, conflicting and incommensurate objective functions. This paper provides an illustrated overview of the state of the art of Interval Programming in the context of multiple objective linear programming models.

"In most real-world situations, problems are characterized by multiple, conflicting and incommensurate axes of evaluation. Moreover, in most real-world problems the available data is inexistent or scarce, difficult to obtain or estimate, the system is subject to changes, etc.
Therefore, mathematical programming models for decision support must bear, besides multiple and conflicting objective functions, the uncertainty associated with the model coefficients. There are several approaches to tackle uncertainty in mathematical programming models. In this context, interval programming possesses some interesting characteristics because it does not
require the specification or the assumption of probabilistic distributions or possibilistic distributions. The interval programming approach assumes that the ranges of variation of some (or all) coefficients which allow specifying a model are known. Interval programming methods have been used to tackle specific issues in multiple objective linear programming (MOLP): some deal with uncertainty in the objective functions, others handle uncertainty both in the objective functions and in the RHS of the constraints and others deal with uncertainty in all the coefficients of the model (see an illustrated overview of these methods in [5]).
In this paper we propose an approach for MOLP problems with interval coefficients that deals with the uncertainty in all the coefficients of the model."

An economy-energy-environment (E3) multiple objective model based on the linear structure of inter-industry production linkages is presented. Axes of evaluation consistent with sustainable energy strategies, economic growth, social welfare and environmental friendliness are explicitly considered. The aim of this study is to provide decision-makers with a comprehensive model which allows assessing environmental burdens (global warming potential and acidification potential) with respect to changes in economic activities associated with distinct policy measures.

An economy-energy-environment (E3) multiple objective model based on the linear structure of inter-industry production linkages is presented. Axes of evaluation consistent with sustainable energy strategies, economic growth, social welfare and environmental friendliness are explicitly considered. The aim of this study is to provide decision-makers with a comprehensive model which allows assessing environmental burdens (global warming potential and acidification potential) with respect to changes in economic activities consistent with distinct policy measures.

"In most real-world situations, the coefficients of decision support models are not exactly known. In this context, it is convenient to consider an extension of traditional mathematical programming models incorporating the intrinsic uncertainty, without assuming the exactness of the model coefficients.
Interval programming is one of the tools to tackle uncertainty in mathematical programming models. This paper provides an overview of the state of the art of Interval Programming in the context of multiple objective linear programming models, paying special attention to the optimizing approach."

An economy-energy-environment multiple objective model based on the linear structure of inter-industry production linkages is presented. Axes of evaluation consistent with sustainable energy strategies, economic growth, social welfare and environmental friendliness are explicitly considered. The aim of this study is to provide decision-makers with a comprehensive model which allows assessing environmental burdens (global warming potential and acidification potential) with respect to changes in economic activities consistent with distinct policy measures.

"An economy–energy–environment multiple objective model based on the linear structure of inter-industry production linkages is presented.Axes of evaluation consistent with sustainable energy strategies, economic growth, social
welfare and environmental friendliness are explicitly considered.The aim of this study is to provide decision-makers with a comprehensive model which allows to assess environmental burdens (global warming potential and acidification potential) with respect to changes in economic activities consistent with distinct policy measures."

The conventional transportation problem usually involves the transportation of goods from several supply points to different demand points and considers the minimization of the total transportation costs. The transportation problem is a special case of linear programming models, following a particular mathematical structure, which has a wide range of potential practical applications, namely in logistic systems, manpower planning, personnel allocation, inventory control, production planning and location of new facilities. However, in reality,the transportation problem usually involves multiple, conflicting, and incommensurable objective functions, being called the multiobjective transportation problem. Several methods have been developed for solving this sort of problems with the assumption of precise information regarding sources, destinations and crisp coefficients for the objective function coefficients. Nevertheless, when dealing with real-life transportation problems, these circumstances may not be verified, since the transportation costs may vary as well as supply and demand requirements. Therefore, different approaches for dealing with inexact coefficients in transportation problems have been proposed in scientific literature, namely with the help of fuzzy and interval programming techniques. This paper is aimed at providing a short critical review of some interval programming techniques for solving this particular type of problems.

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. 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.
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. 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. 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.
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. 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.
Interval programming is an interesting approach to tackle uncertainty in mathematical programming models, since it does not require the specification of the probabilistic distributions (as in stochastic programming) or the possibilistic distributions (as in fuzzy programming) of the model coefficients. Interval programming just assumes that information about the range of variation of the uncertain coefficients is available. One of the main goals of this dissertation consisted in developing an interactive method for
multiobjective linear programming problems with interval coefficients, to study the interactions between the national economy, the energy system and the environmental
impacts, by supporting the decision-makers in the identification of robust solutions, that is solutions with good performance for different model coefficient settings.
An extensive work of data gathering has been made in order to develop a national realistic model. Some illustrative results, obtained by using that interactive method are analysed, emphasizing the usefulness of the proposed approach to provide decision aid to decision-makers.