ORCID Profile
0000-0003-3102-2766
Current Organisations
NICTA
,
Australian National University
,
Los Alamos National Laboratory
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Publisher: IEEE
Date: 2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2016
Publisher: Springer Science and Business Media LLC
Date: 12-04-2018
Publisher: IEEE
Date: 17-07-2022
Publisher: IEEE
Date: 14-12-2021
Publisher: IEEE
Date: 04-2012
DOI: 10.1109/DCC.2012.33
Publisher: Springer Science and Business Media LLC
Date: 14-06-2018
Publisher: Elsevier BV
Date: 07-2016
Publisher: Springer Science and Business Media LLC
Date: 06-08-2012
Publisher: Elsevier BV
Date: 2022
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 07-2020
Abstract: This paper studies mixed-integer nonlinear programs featuring disjunctive constraints and trigonometric functions and presents a strengthened version of the convex quadratic relaxation of the optimal transmission switching problem. We first characterize the convex hull of univariate quadratic on/off constraints in the space of original variables using perspective functions. We then introduce new tight quadratic relaxations for trigonometric functions featuring variables with asymmetrical bounds. These results are used to further tighten recent convex relaxations introduced for the optimal transmission switching problem in power systems. Using the proposed improvements, along with bound propagation, on 23 medium-sized test cases in the PGLib benchmark library with a relaxation gap of more than 1%, we reduce the gap to less than 1% on five instances. The tightened model has promising computational results when compared with state-of-the-art formulations.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2017
Publisher: Elsevier BV
Date: 11-2015
Publisher: Elsevier BV
Date: 08-2010
Publisher: Elsevier BV
Date: 08-2010
Publisher: Author(s)
Date: 2019
DOI: 10.1063/1.5090004
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 02-2014
Abstract: A common structure in convex mixed-integer nonlinear programs (MINLPs) is separable nonlinear functions. In the presence of such structures, we propose three improvements to the outer approximation algorithms. The first improvement is a simple extended formulation, the second is a refined outer approximation, and the third is a heuristic inner approximation of the feasible region. As a side result, we exhibit a simple ex le where a classical implementation of the outer approximation would take an exponential number of iterations, whereas it is easily solved with our modifications. These methods have been implemented in the open source solver Bonmin and are available for download from the Computational Infrastructure for Operations Research project website. We test the effectiveness of the approach on three real-world applications and on a larger set of models from an MINLP benchmark library. Finally, we show how the techniques can be extended to perspective formulations of several problems. The proposed tools lead to an important reduction in computing time on most tested instances.
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 11-2016
Abstract: Expansion of natural gas networks is a critical process involving substantial capital expenditures with complex decision-support requirements. Given the nonconvex nature of gas transmission constraints, global optimality and infeasibility guarantees can only be offered by global optimisation approaches. Unfortunately, state-of-the-art global optimisation solvers are unable to scale up to real-world size instances. In this study, we present a convex mixed-integer second-order cone relaxation for the gas expansion planning problem under steady-state conditions. The underlying model offers tight lower bounds with high computational efficiency. In addition, the optimal solution of the relaxation can often be used to derive high-quality solutions to the original problem, leading to provably tight optimality gaps and, in some cases, global optimal solutions. The convex relaxation is based on a few key ideas, including the introduction of flux direction variables, exact McCormick relaxations, on/off constraints, and integer cuts. Numerical experiments are conducted on the traditional Belgian gas network, as well as other real larger networks. The results demonstrate both the accuracy and computational speed of the relaxation and its ability to produce high-quality solutions.
Publisher: Springer International Publishing
Date: 2016
Publisher: Springer International Publishing
Date: 2015
Publisher: Springer Science and Business Media LLC
Date: 27-04-2013
Publisher: Springer Science and Business Media LLC
Date: 02-07-2019
Publisher: IEEE
Date: 07-2016
Publisher: Springer Science and Business Media LLC
Date: 15-10-2017
Publisher: Springer International Publishing
Date: 2018
Publisher: Author(s)
Date: 2019
DOI: 10.1063/1.5089984
Publisher: Elsevier BV
Date: 12-2020
No related grants have been discovered for Hassan Hijazi.