<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Baptista, Susana</style></author><author><style face="normal" font="default" size="100%">Barbosa-povoa, Ana Paula</style></author><author><style face="normal" font="default" size="100%">Escudero, Laureano</style></author><author><style face="normal" font="default" size="100%">Gomes, Maria Isabel</style></author><author><style face="normal" font="default" size="100%">Pizarro, Celeste</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Metaheuristic for Solving Large-Scale Two-Stage Stochastic Mixed 0-1 Programs with the Time Stochas- tic Dominance Risk Averse Strategy</style></title><secondary-title><style face="normal" font="default" size="100%">12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering. </style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><related-urls><url><style face="normal" font="default" size="100%">https://docentes.fct.unl.pt/sites/default/files/mirg/files/escape25.pdf</style></url></related-urls></urls><publisher><style face="normal" font="default" size="100%">Elsevier</style></publisher><pub-location><style face="normal" font="default" size="100%">Copenhagen, Denmark  </style></pub-location><pages><style face="normal" font="default" size="100%">857-862</style></pages><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Supply Chain Design problems often result into multiperiod stochastic mixed integer problems that are hard to solve. In this paper we propose a metaheuristic algorithm as a specialization for two- stage problems of the so-named Fix-and-Relax Algorithm presented previously for solving large- scale multiperiod stochastic mixed 0-1 optimization problems under a time stochastic dominance risk averse strategy, so-named TSD. Some computational experience is presented.&lt;/p&gt;
</style></abstract></record></records></xml>