Results 51 to 60 of about 1,159 (105)
A Survey on Mixed-Integer Programming Techniques in Bilevel Optimization
EURO Journal on Computational Optimization, 2021 Bilevel optimization is a field of mathematical programming in which some variables are constrained to be the solution of another optimization problem. As a consequence, bilevel optimization is able to model hierarchical decision processes.
Thomas Kleinert +3 more
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Computing Integral Solutions of Complementarity Problems [PDF]
AMS classifications: 90C33, 90C26, 91B50.Discrete set;complementarity problem;algorithm ...
Laan, G. van der +2 more
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Performance Bounds For Co-/Sparse Box Constrained Signal Recovery
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2019 The recovery of structured signals from a few linear measurements is a central point in both compressed sensing (CS) and discrete tomography. In CS the signal structure is described by means of a low complexity model e.g. co-/sparsity.
Kuske Jan, Petra Stefania
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Joint location and pricing within a user-optimized environment
EURO Journal on Computational Optimization, 2020 In the design of service facilities, whenever the behaviour of customers is impacted by queueing or congestion, the resulting equilibrium cannot be ignored by a firm that strives to maximize revenue within a competitive environment.
Teodora Dan +2 more
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EURO Journal on Computational Optimization, 2016 For many practical applications it is important to determine not only a numerical approximation of one but a representation of the whole set of globally optimal solutions of a non-convex optimization problem.
Gabriele Eichfelder +2 more
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EURO Journal on Computational Optimization, 2020 The concept of leader-follower (or Stackelberg) equilibrium plays a central role in a number of real-world applications bordering on mathematical optimization and game theory.
Nicola Basilico +3 more
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Alternative SDP and SOCP approximations for polynomial optimization
EURO Journal on Computational Optimization, 2019 In theory, hierarchies of semidefinite programming (SDP) relaxations based on sum of squares (SOS) polynomials have been shown to provide arbitrarily close approximations for a general polynomial optimization problem (POP).
Xiaolong Kuang +3 more
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A bounded degree SOS hierarchy for polynomial optimization
EURO Journal on Computational Optimization, 2017 We consider a new hierarchy of semidefinite relaxations for the general polynomial optimization problem (P):f∗=min{f(x):x∈K} on a compact basic semi-algebraic set K⊂Rn.
JeanB. Lasserre +2 more
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A class of null space conditions for sparse recovery via nonconvex, non-separable minimizations
Results in Applied Mathematics, 2019 For the problem of sparse recovery, it is widely accepted that nonconvex minimizations are better than ℓ1 penalty in enhancing the sparsity of solution.
Hoang Tran, Clayton Webster
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Sufficient pruning conditions for MINLP in gas network design
EURO Journal on Computational Optimization, 2017 One-quarter of Europe’s energy demand is provided by natural gas distributed through a vast pipeline network covering the whole of Europe. At a cost of 1 million Euros per kilometer the extension of the European pipeline network is already a multi ...
Jesco Humpola, Felipe Serrano
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