55 Result(s)
within
Ignacio E. Grossmann
English
Operations Research/Decision Theory
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Article
Open AccessExtensions to generalized disjunctive programming: hierarchical structures and first-order logic
Optimization problems with discrete–continuous decisions are traditionally modeled in algebraic form via (non)linear mixed-integer programming. A more systematic approach to modeling such systems is to use gen...
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Article
Open AccessDecomposition methods for multi-horizon stochastic programming
Multi-horizon stochastic programming includes short-term and long-term uncertainty in investment planning problems more efficiently than traditional multi-stage stochastic programming. In this paper, we exploi...
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Article
Convex mixed-integer nonlinear programs derived from generalized disjunctive programming using cones
We propose the formulation of convex Generalized Disjunctive Programming (GDP) problems using conic inequalities leading to conic GDP problems. We then show the reformulation of conic GDPs into Mixed-Integer C...
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Article
Open AccessIterative MILP algorithm to find alternate solutions in linear programming models
We address in this paper linear programming (LP) models in which it is desired to find a finite set of alternate optima. An LP may have multiple alternate solutions with the same objective value or with increa...
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Article
Surface facility optimization for combined shale oil and gas development strategies
In the context of a global energy transition, oil and gas will remain an important part of the energy mix, especially in develo** countries. The challenge of energy companies is to adapt to a changing policy...
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Article
Pipeline network design for gathering unconventional oil and gas production using mathematical optimization
The optimal design of gathering networks for the unconventional oil and gas production is a relevant problem, particularly with the shale boom. In this work, we address a network design problem in which the ma...
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Article
Alternative regularizations for Outer-Approximation algorithms for convex MINLP
In this work, we extend the regularization framework from Kronqvist et al. (Math Program 180(1):285–310, 2020) by incorporating several new regularization functions and develop a regularized single-tree search...
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Article
Recent contributions to the optimal design of pipeline networks in the energy industry using mathematical programming
The optimal design of pipeline networks has inspired process systems engineers and operations research practitioners since the earliest times of mathematical programming. The nonlinear equations governing pres...
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Article
Pyomo.GDP: an ecosystem for logic based modeling and optimization development
We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—...
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Article
A biographical review of the research and impacts of Marco Duran
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Article
State of the art methods for combined water and energy systems optimisation in Kraft pulp mills
This paper presents a state-of-the-art overview of water and energy optimisation methods with applications to Kraft pulp mills. The main conclusions are highlighted, and several research gaps are identified an...
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Article
Sample average approximation for stochastic nonconvex mixed integer nonlinear programming via outer-approximation
We propose a sample average approximation-based outer-approximation algorithm (SAAOA) that can address nonconvex two-stage stochastic programs (SP) with any continuous or discrete probability distributions. Pr...
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Article
Electric power infrastructure planning under uncertainty: stochastic dual dynamic integer programming (SDDiP) and parallelization scheme
We address the long-term planning of electric power infrastructure under uncertainty. We propose a Multistage Stochastic Mixed-integer Programming formulation that optimizes the generation expansion to meet th...
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Article
A computationally useful algebraic representation of nonlinear disjunctive convex sets using the perspective function
Nonlinear disjunctive convex sets arise naturally in the formulation or solution methods of many discrete–continuous optimization problems. Often, a tight algebraic representation of the disjunctive convex set...
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Article
Open AccessCorrection to: Implementation of RTO in a large hydrogen network considering uncertainty
Correction to: Optimization and Engineering https://doi.org/10.1007/s11081-019-09444-3
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Article
A preface to the special issue on enterprise-wide optimization
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Article
Open AccessImplementation of RTO in a large hydrogen network considering uncertainty
This paper describes the problems associated with the implementation of a real-time optimization (RTO) decision support tool, for the operation of a large scale hydrogen network of an oil refinery. In addition...
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Article
Multiperiod optimization model for oilfield production planning: bicriterion optimization and two-stage stochastic programming model
In this work, we present different tools of mathematical modeling that can be used in oil and gas industry to help improve the decision-making for field development, production optimization and planning. First...
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Article
A finite \(\epsilon \)-convergence algorithm for two-stage stochastic convex nonlinear programs with mixed-binary first and second-stage variables
In this paper, we propose a generalized Benders decomposition-based branch and bound algorithm (GBDBAB) to solve two-stage convex mixed-binary nonlinear stochastic programs with mixed-binary variables in both ...
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Article
A generalized Benders decomposition-based branch and cut algorithm for two-stage stochastic programs with nonconvex constraints and mixed-binary first and second stage variables
In this paper, we propose a generalized Benders decomposition-based branch and cut algorithm for solving two stage stochastic mixed-integer nonlinear programs (SMINLPs) with mixed binary first and second stage...
