Efficient formulation and solution methods

Achieving Emission-Reduction Goals: Multi-Period Power-System Expansion under Short-Term Operational Uncertainty
Stochastic adaptive robust optimization is capable of handling short-term uncertainties in demand and variable renewable-energy sources …
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Achieving Emission-Reduction Goals: Multi-Period Power-System Expansion under Short-Term Operational Uncertainty
The p-Lagrangian relaxation for separable nonconvex MIQCQP problems
This paper presents a novel technique to compute Lagrangian bounds for nonconvex mixed-integer quadratically constrained quadratic …
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The p-Lagrangian relaxation for separable nonconvex MIQCQP problems
A two stage stochastic programming for asset protection routing and a solution algorithm based on the Progressive Hedging algorithm
In this paper, a two-stage stochastic programming model is developed for the asset protection routing problem (APRP) to be employed in …
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A two stage stochastic programming for asset protection routing and a solution algorithm based on the Progressive Hedging algorithm
Efficient formulation for transportation scheduling of single refinery multiproduct pipelines
Multiproduct pipeline transportation scheduling is a complex operations research problem that is characterized by the movement of the …
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Efficient formulation for transportation scheduling of single refinery multiproduct pipelines
Wasserstein-Distance-Based Temporal Clustering for Capacity-Expansion Planning in Power Systems
As variable renewable energy sources are steadily incorporated in European power systems, the need for higher temporal resolution in …
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Combining Progressive Hedging with a Frank--Wolfe Method to Compute Lagrangian Dual Bounds in Stochastic Mixed-Integer Programming
We present a new primal-dual algorithm for computing the value of the Lagrangian dual of a stochastic mixed-integer program (SMIP) …
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Combining Progressive Hedging with a Frank--Wolfe Method to Compute Lagrangian Dual Bounds in Stochastic Mixed-Integer Programming
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