7 resultados para pareto inefficiency

em Universidad de Alicante


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Presentation submitted to PSE Seminar, Chemical Engineering Department, Center for Advanced Process Design-making (CAPD), Carnegie Mellon University, Pittsburgh (USA), October 2012.

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This multidisciplinary study concerns the optimal design of processes with a view to both maximizing profit and minimizing environmental impacts. This can be achieved by a combination of traditional chemical process design methods, measurements of environmental impacts and advanced mathematical optimization techniques. More to the point, this paper presents a hybrid simulation-multiobjective optimization approach that at once optimizes the production cost and minimizes the associated environmental impacts of isobutane alkylation. This approach has also made it possible to obtain the flowsheet configurations and process variables that are needed to manufacture isooctane in a way that satisfies the above-stated double aim. The problem is formulated as a Generalized Disjunctive Programming problem and solved using state-of-the-art logic-based algorithms. It is shown, starting from existing alternatives for the process, that it is possible to systematically generate a superstructure that includes alternatives not previously considered. The optimal solution, in the form a Pareto curve, includes different structural alternatives from which the most suitable design can be selected. To evaluate the environmental impact, Life Cycle Assessment based on two different indicators is employed: Ecoindicator 99 and Global Warming Potential.

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The aim of this study was to explore the experience of service providers in Spain regarding their daily professional encounters with battered immigrant women and their perception of this group’s help-seeking process and the eventual abandonment of the same. Twenty-nine in-depth interviews and four focus group discussions were conducted with a total of 43 professionals involved in providing support to battered immigrant women. We interviewed social workers, psychologists, intercultural mediators, judges, lawyers, and public health professionals from Spain. Through qualitative content analysis, four categories emerged: (a) frustration with the victim’s decision to abandon the help-seeking process, (b) ambivalent positions regarding differences between immigrant and Spanish women, (c) difficulties in the migratory process that may hinder the help-seeking process, and (d) criticisms regarding the inefficiency of existing resources. The four categories were cross-cut by an overarching theme: helping immigrant women not to abandon the help-seeking process as a chronicle of anticipated failure. The main reasons that emerged for abandoning the help-seeking process involved structural factors such as economic dependence, loss of social support after leaving their country of origin, and limited knowledge about available resources. The professionals perceived their encounters with battered immigrant women to be frustrating and unproductive because they felt that they had few resources to back them up. They felt that despite the existence of public policies targeting intimate partner violence (IPV) and immigration in Spain, the resources dedicated to tackling gender-based violence were insufficient to meet battered immigrant women’s needs. Professionals should be trained both in the problem of IPV and in providing support to the immigrant population.

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Multiobjective Generalized Disjunctive Programming (MO-GDP) optimization has been used for the synthesis of an important industrial process, isobutane alkylation. The two objective functions to be simultaneously optimized are the environmental impact, determined by means of LCA (Life Cycle Assessment), and the economic potential of the process. The main reason for including the minimization of the environmental impact in the optimization process is the widespread environmental concern by the general public. For the resolution of the problem we employed a hybrid simulation- optimization methodology, i.e., the superstructure of the process was developed directly in a chemical process simulator connected to a state of the art optimizer. The model was formulated as a GDP and solved using a logic algorithm that avoids the reformulation as MINLP -Mixed Integer Non Linear Programming-. Our research gave us Pareto curves compounded by three different configurations where the LCA has been assessed by two different parameters: global warming potential and ecoindicator-99.

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A Mass Customisation model is discussed as a competitive positioning strategy in the marketplace adding value to the customer’s end-use. It includes the user as part of the construction process responding to the customer’s demands and wishes. To the present day, almost all proposals for Mass Customisation have been focused on the design phase and single family houses. The reality is that the processes carried out in the work execution are so inefficient that the costs of the Mass Customisation models are assumed by the customer and they do not offer solutions that support the change management. Furthermore, this inefficiency often makes Mass Customisation unfeasible in terms of deadlines and site management. Therefore, the present proposal focuses on achieving the paradigm of Mass Customisation in the traditional residential construction complementary to the existing proposals in the design phase. All this through the proposal of a framework for the integral management in the work execution, which will address change management introduced by the users offering an efficient and productive model that reduces costs in the process. This model will focus on the synergy between different strategies, techniques and technologies currently used in the construction management (such as Lean Construction or Six Sigma), together with, other strategies and technologies that have proven to be valid solutions in other fields (such as Business Process Management, Service Oriented Architecture, etc.).

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The main goal of this paper is to analyse the sensitivity of a vector convex optimization problem according to variations in the right-hand side. We measure the quantitative behavior of a certain set of Pareto optimal points characterized to become minimum when the objective function is composed with a positive function. Its behavior is analysed quantitatively using the circatangent derivative for set-valued maps. Particularly, it is shown that the sensitivity is closely related to a Lagrange multiplier solution of a dual program.