Computational Optimization and Applications

, Volume 62, Issue 3, pp 609–611 | Cite as

COAP 2014 Best Paper Prize


Each year, the editorial board of Computational Optimization and Applications (COAP) selects a paper from the preceding year’s publications for the Best Paper Award. In 2014, 87 papers were published by COAP. The recipients of the 2014 Best Paper Award are Daniel Espinoza of the University of Chile and Eduardo Moreno of the Adolfo Ibáñez University, Chile, for their paper “A primal-dual aggregation algorithm for minimizing conditional value-at-risk in linear programs” published in volume 59 pages 617–638. This article highlights the research related to the award winning paper.

Nowadays, an increasing variety of stochastic optimization problems are tackled using the sample average approximation method [5, 8]. Using this technique, a given stochastic optimization problem with an underlying (possibly continuous or even unknown) probability distribution can be approximated by solving a series of sampledproblems which have, in turn, an underlying discrete distribution. Its accuracy...


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© Springer Science+Business Media New York 2015

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