In the last few decades there has been a massive growth in the Waste of Electric and ElectronicEquipment (WEEE). Part of these residues was already properly treated in some countries, but the lack of environmentally friendly options forced the European Union (EU) to take action. Two EU directives were created based on reduction, reutilization and recycling of WEEE. The need to properly designrecoverynetworks for such products appears as mandatory, where not only the economic aspects should be accounted for but also the environmental ones. The present paper addresses this problem and presents a generic optimization model for the design and planning of a recovery and treatment network of WEEE, minimizing both the costs and the environmental impacts that arise from the activity performed.

The model is applied to the real case of Amb3E, the Portuguese Association for the Management of Waste of Electric and ElectronicEquipment. Since its formation, in 2006, this organization has been registering an immense growth in the volume of residue collected, and faces now the necessity of reformulating its recoverynetwork. Both the actual cost structure and the best possible cost structure for Amb3E, given by the optimization of the model, are analyzed. These two scenarios are compared in order to turn clear the differences between them and to assess how the recoverynetwork of Amb3E can be improved through optimization. A similar analysis is performed from an environmental impacts perspective.

Under the framework of the European project named COPOWER, the possibility to partially substitute coal used in a 243 MWth Power Plant by biomass and non-hazardous wastes for the production of electricity and steam was assessed. Three combustion scenarios were studied, based on the combustion tests performed in a Power Plant located in Duisburg (Germany): Scenario 0 (Sc0) – combustion of coal; Scenario 1 (Sc1) – combustion of coal + sewage sludge (SS) + meat and bone meal (MBM); Scenario 2 (Sc2) – coal + SS + wood pellets (WP). An environmental and socio-economic assessment of these three scenarios was performed. In the environmental point of view, Sc0 was the worst scenario, mainly due to the emission of greenhouse gases (GHG). Sc1 was the best scenario, mainly due to the reduction of GHG emission, eutrophication chemical species and ozone depletion gases. In the socio-economic point of view, Sc0 was the worst scenario, mainly due to the absence of GHG abatement, and Sc1 was the best scenario due to the best cost of electricity production and negative cost of avoided emissions.

Domain Specific Languages (DSLs) are claimed to increase productivity, while reducing the required maintenance and programming expertise. In this context, DSL usability by domain experts is a key factor for its successful adoption. Evidence that support those improvement claims is mostly anecdotal. Our systematic literature review showed that a usability evaluation was often skipped, relaxed, or at least omitted from papers reporting the development of DSLs. The few exceptions mostly take place at the end of the development process where fixing problems identified is too expensive. We argue that a systematic approach based on User Interface experimental validation techniques should be used to assess the impact of the new DSLs. The rationale is that assessing important and specially tailored usability attributes for DSLs early in language construction will ultimately foster a higher productivity of the DSL users. This paper, besides discussing the quality criteria, proposes a development and evaluation process that can be used to achieve usable DSLs in a better way.

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The mechanism proposed by Evans to justify the selectivity obtained in Lewis acid catalyzed Diels-Alder reactions of cyclopentadiene with acyloxazolidinones has been generalized and used in the rationalization of selectivities obtained in many other systems. However, we recently proposed an alternative mechanism, on the basis of open-chain mono- and bicomplexes, that avoids the need for chelates and explains the selectivity obtained by Evans. In this manuscript we apply our proposal to the catalyzed conjugated addition of amines to acylimidazolidinones, reported by Cardillo, and we clearly show that aluminum chelates are not involved in the reaction, as they induce no selectivity, while Cardillo observed high experimental selectivities. Our data equally show that bicomplexes with carbonyl parallel orientation, proposed by Cardillo to justify the experimental selectivity with nonchelating Lewis acids, indeed induce the opposite selectivity and have also to be dismissed. On the other hand, our mechanistic proposal allows for the full rationalization of the data obtained by Cardillo with aluminum, boron, or zinc Lewis acids and supports our previous proposal on DA cycloadditions of dienes to Evans chiral auxiliary derivatives.

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Optimized supply chains, both economically as well as environmentally, are significant instruments to be adopted by companies if they want to succeed in the current competitive world. However, without the support of decision tools to help, at least approximately, the integration of these two aspects in the company’s decision making such aim is difficult to reach. The purpose of this study is to develop a mixed integer linear programming model (MILP), which allows the optimization of closed loop supply chains, considering not only economical aspects, but also environmental ones. The model developed was applied to a Portuguese company where their logistic network structure was redesigned.

The efficient design and operation of supply chains with return flows represent a major optimization challenge, given the high number of factors involved and their intricate interactions. In particular, the quality level of the return products has strong economic and societal implications and depends greatly on the type of product (glass, paper, electronic, oil, etc) and on the degree of consumers’ readiness, frequently promoted by various kinds of awareness raising campaigns. A multi-product multi-period model was previously developed by the authors [1] for the closed-loop supply chain (CLSC) design and planning, where strategic and tactical decisions were comprehensively considered. This model is now being extended to handle the uncertainty related to the quality of the returned products, which at this stage is modeled by a two-stage scenario-based stochastic approach. General strategies to solve optimization problems involving uncertainty tend to exhibit poor computational performance, due to the problem NP-hard complexity, which tends to worsen with the problem size. Therefore and, in addition, a model performance solution enhancement is also being explored. To increase the efficiency of the solution approach, an alternative representation to some of the integer variables employed in the mathematical formulation was developed, which is tested by means of computational experiments being performed on illustrative real sized examples.

Domain Specific Languages (DSLs) are claimed to increment productivity, while reducing the required maintenance and programming expertise. In this context, DSLs usability is a key factor for its successful adoption.

In this paper, we propose a systematic approach based on User Interfaces Experimental validation techniques to assess the impact of the introduction of DSLs on the productivity of domain experts. To illustrate this evaluation approach we present a case study of a DSL for High Energy Physics (HEP).

The DSL on this case study, called Pheasant (PHysicist’s EAsy Analysis Tool), is assessed in contrast with a pre-existing baseline, using General Purpose Languages (GPLs) such as C++. The comparison combines quantitative and qualitative data, collected with users from a real-world setting. Our assessment includes Physicists with programming experience with two profiles; ones with no experience with the previous framework used in the project and other experienced.

This work’s contribution highlights the problem of the absence of systematic approaches for experimental validation of DSLs. It also illustrates how an experimental approach can be used in the context of a DSL evaluation during the Software Languages Engineering activity, with respect to its impact on effectiveness and efficiency.

The present work aims to develop a decision supporting tool to help the decision making process related to the planning of waste collection systems. Such systems involve more than one depot and the objective is to define the delimitation of service areas and the vehicles routes. The problem is modelled as a multi-product, multi-depot vehicle routing problem. A hybrid method that combines exact formulations with heuristic procedures is developed and applied to a real recyclable collection system whose managers want to restructure the current service areas as well as the vehicle routes used to collect three types of recyclable materials.

This paper is focused on the delimitation of service areas and on vehicle routes definition in recyclable waste collection systems with more than one depot. Three types of materials have to be collected in separated routes, so the problem is modelled as a multi-product, multi-depot vehicle routing problem. A hybrid method is developed where a MIP solver is embedded inside a heuristic framework. The effectiveness of this method is tested by comparing the results obtained for some test instances when solved only by an exact formulation. The hybrid method is then applied to a medium size problem based on a real recyclable waste collection system.

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