M
Miguel F. Anjos
Researcher at University of Edinburgh
Publications - 214
Citations - 4050
Miguel F. Anjos is an academic researcher from University of Edinburgh. The author has contributed to research in topics: Semidefinite programming & Relaxation (approximation). The author has an hindex of 27, co-authored 201 publications receiving 3333 citations. Previous affiliations of Miguel F. Anjos include HEC Montréal & University of Southampton.
Papers
More filters
Journal ArticleDOI
Tight Mixed Integer Linear Programming Formulations for the Unit Commitment Problem
TL;DR: In this article, the authors examined the polytope of feasible power generation schedules in the unit commitment (UC) problem and provided computational results comparing formulations for the UC problem commonly found in the literature.
BookDOI
Handbook on semidefinite, conic and polynomial optimization
Miguel F. Anjos,Jean B. Lasserre +1 more
TL;DR: This paper presents an introduction to Semidefinite, Conic and Polynomial Optimization, and discusses Relaxations for Some Combinatorial Optimization Problems, and the State of theArt in Conic Optimization Software.
Journal ArticleDOI
A System Architecture for Autonomous Demand Side Load Management in Smart Buildings
TL;DR: This architecture can encapsulate the system functionality, assure the interoperability between various components, allow the integration of different energy sources, and ease maintenance and upgrading, and allows seamless integration of diverse techniques for online operation control, optimal scheduling, and dynamic pricing.
Journal ArticleDOI
A Procurement Market Model for Reactive Power Services Considering System Security
TL;DR: A reactive power procurement market model is proposed here taking into consideration system security aspects, and the selected set of generators and zonal price components are determined by solving an OPF-based auction to maximize a societal advantage function.
Journal ArticleDOI
A semidefinite optimization approach for the single-row layout problem with unequal dimensions
TL;DR: A semidefinite programming (SDP) relaxation is constructed providing a lower bound on the optimal value of the one-dimensional space-allocation problem (ODSAP), also known as the single-row facility layout problem, which consists in finding an optimal linear placement of facilities with varying dimensions on a straight line.