Decomposition Techniques in Mathematical Programming: Engineering and Science Applications

By Antonio J. Conejo. 2006

517 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a6cb4f3b8cb75e77ade48ee537fd8941b4926689

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Citations in the corpus

Consensus + Innovations Approach for Distributed Multiagent Coordination in a Microgrid (2015, methodology): “Prior distributed approaches for scheduling generation and/or load are mostly based on Lagrangian and augmented Lagrangian relaxation type methods [10].”
Two-Stage Robust Generation Expansion Planning: A Mixed Integer Linear Programming Model (2014, background): “The convergence of Benders decomposition is guaranteed when the envelope of the subproblem is convex with respect to complicating variables as discussed in [42].”
Decentralized Multi-Area Dynamic Economic Dispatch Using Modified Generalized Benders Decomposition (2016, methodology): “The LR-BD method refers to the LR dual algorithm with quadratic stabilization terms, which is also known as the bundle method [8], [28].”
Peer-to-peer and community-based markets: A comprehensive review (2018, background): “tion problem, in a coordinated manner. The reciprocity constraints (1c) are linking constraints that insure that coordination. The literature proposes the use of decentralized optimization techniques [65,67,70,71]. Decomposition techniques such as Lagrangian relaxation, consensus Alternating Directi”
Integer programming techniques for educational timetabling (2017, methodology): “However, to achieve good/optimal solutions through exact methods may be possible only when the timetabling problem is small or when advanced techniques of formulation, such as Column Generation [16], Cuts [17, 18], and Decomposition [19] are applied.”
Extended Benders Decomposition for Two-Stage SCUC (2010, background): “Benders cut applications are based on a prerequisite that the subproblem corresponding to the second stage is LP or convex NLP [1].”
A bilevel model for electricity retailers' participation in a demand response market environment (2013, methodology): “The equivalence of the KKT formulation and the one in Section 2.2.1 is guaranteed by the linearity of the latter one, which implies that solutions of the optimisation problem are also solution of the KKT system of equations and vice versa, see Conejo et al. (2006).”
A Benders decomposition approach for a combined heat and power economic dispatch (2013, background): “, they make the problem more difficult to solve [32].”
Robust Energy Management for Microgrids With High-Penetration Renewables (2012, unknown): “The features of strong duality and separability imply that Lagrangian relaxation and dual decomposition are applicable to yield a decentralized algorithm; see also related techniques in power systems [22] and communication networks [23], [24].”