18 resultados para Intergovernmental personnel programs


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We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.

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We consider risk-averse convex stochastic programs expressed in terms of extended polyhedral risk measures. We derive computable con dence intervals on the optimal value of such stochastic programs using the Robust Stochastic Approximation and the Stochastic Mirror Descent (SMD) algorithms. When the objective functions are uniformly convex, we also propose a multistep extension of the Stochastic Mirror Descent algorithm and obtain con dence intervals on both the optimal values and optimal solutions. Numerical simulations show that our con dence intervals are much less conservative and are quicker to compute than previously obtained con dence intervals for SMD and that the multistep Stochastic Mirror Descent algorithm can obtain a good approximate solution much quicker than its nonmultistep counterpart. Our con dence intervals are also more reliable than asymptotic con dence intervals when the sample size is not much larger than the problem size.

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Purpose – This case study presents an impact assessment of Corporate Social Responsibility (CSR) programs of the TFM Company in order to understand how they contribute to the sustainable development of communities in areas in which they operate. Design/Methodology/Approach - Data for this study was collected using qualitative data methods that included semi-structured interviews and Focus Group Discussions most of them audio and video recorded. Documentary analysis and a field visit were also undertaken for the purpose of quality analysis of the CSR programs on the terrain. Data collected was analyzed using the Seven Questions to sustainability (7Qs) framework, an evaluation tool developed by the Mining, Minerals and Sustainable Development (MMSD) North America chapter. Content analysis method was on the other hand used to examine the interviews and FGDs of the study participants. Findings - Results shows that CSR programs of TFM SA do contribute to community development, as there have been notable changes in the communities’ living conditions. But whether they have contributed to sustainable development is not yet the case as programs that enhance the capacity of communities and other stakeholders to support these projects development beyond the implementation stage and the mines operation lifetime need to be considered and implemented. Originality/Value – In DRC, there is paucity of information of research studies that focus on impact assessment of CSR programs in general and specifically those of mining companies and their contribution to sustainable development of local communities. Many of the available studies cover issues of minerals and conflict or conflict minerals as mostly referred to. This study addressees this gap.