Víctor M. Albornoz

TL;DR: In this paper, a two-stage stochastic integer programming (SILP) is used to obtain an optimum policy in the capacity expansion planning of a particular thermal-electric power system, which includes the existent uncertainty related to the future availability of the thermal plants currently under operation.

TL;DR: A new MIP model is proposed which determines the best scheduling for all the jobs in the queue, identifying their resource allocation and its execution order to minimize the overall makespan.

TL;DR: This work presents a new zoning method that optimally delineates rectangular homogeneous management zones, using relative variance to guarantee the homogeneity, and relies on an integer linear programming model that is efficiently solved to optimality.

TL;DR: Results obtained from a sensitivity analysis performed to assess the suitability of the model approach and the benefits of representing real variability over time against time homogeneity lead to better understand sow herd dynamics over a finite time-horizon and corresponding performance.

TL;DR: The proposed model considers a medium-term planning horizon and specifically allows optimal replacement and schedule of purchases to be obtained for the first stage, which takes into account sow herd dynamics, housing facilities, reproduction management, herd size with initial and final inventory of sows and uncertain parameters such as litter size, mortality and fertility rates.