Efficient formulation and solution methods

Combining penalty-based and Gauss-Seidel methods for solving stochastic mixed-integer problems
In this paper, we propose a novel decomposition approach (named PBGS) for stochastic mixed-integer programming (SMIP) problems, which …
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Combining penalty-based and Gauss-Seidel methods for solving stochastic mixed-integer problems
A parallelizable augmented Lagrangian method applied to large-scale non-convex-constrained optimization problems
We contribute improvements to a Lagrangian dual solution approach applied to large-scale optimization problems whose objective …
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A parallelizable augmented Lagrangian method applied to large-scale non-convex-constrained optimization problems
Enhancing the normalized multiparametric disaggregation technique for mixed-integer quadratic programming
We propose methods for improving the relaxations obtained by the normalized multiparametric disaggregation technique (NMDT). These …
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Enhancing the normalized multiparametric disaggregation technique for mixed-integer quadratic programming
A strategy based on convex relaxation for solving the oil refinery operations planning problem
Oil refining is one of the most complex activities in the chemical industry due to its nonlinear nature, which ruins the convexity …
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A strategy based on convex relaxation for solving the oil refinery operations planning problem
An enhanced L-Shaped method for optimizing periodic-review inventory control problems modeled via two-stage stochastic programming
This paper presents the development of an enhanced L-Shaped method applied to an inventory management problem that considers a …
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An enhanced L-Shaped method for optimizing periodic-review inventory control problems modeled via two-stage stochastic programming
Accelerating Benders stochastic decomposition for the optimization under uncertainty of the petroleum product supply chain
This paper addresses the solution of a two-stage stochastic programming model for an investment planning problem applied to the …
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Accelerating Benders stochastic decomposition for the optimization under uncertainty of the petroleum product supply chain
A Lagrangean decomposition approach for oil supply chain investment planning under uncertainty with risk considerations
We present a scenario decomposition framework based on Lagrangean decomposition for the multi-product, multi-period, supply investment …
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A Lagrangean decomposition approach for oil supply chain investment planning under uncertainty with risk considerations
Stochastic benders decomposition for the supply chain investment planning problem under demand uncertainty
This paper presents the application of a stochastic Benders decomposition algorithm for the problem of supply chain investment planning …
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