The scenario optimisation approach is a methodology for finding solutions to uncertain convex problems by resorting to a sample of data, which are called “scenarios”. In a min–max set-up, the solution delivered by the scenario approach comes with tight probabilistic guarantees on its risk defined as the probability that an empirical cost threshold will be exceeded when the scenario-based solution is adopted. While the standard theory of scenario optimisation has related the risk of the data-based solution to the number of optimisation variables, a more recent approach, called the “wait-and-judge” scenario approach, enables the user to assess the risk of the solution in a data-dependent way, based on the number of decisive scenarios (“support scenarios”). The aim of this paper is to illustrate the potentials of the wait-and-judge approach for min–max sample-based design and we shall consider to this purpose an antenna array design problem.

The wait-and-judge scenario approach applied to antenna array design

Carè, Algo
;
Campi, Marco C.
2019

Abstract

The scenario optimisation approach is a methodology for finding solutions to uncertain convex problems by resorting to a sample of data, which are called “scenarios”. In a min–max set-up, the solution delivered by the scenario approach comes with tight probabilistic guarantees on its risk defined as the probability that an empirical cost threshold will be exceeded when the scenario-based solution is adopted. While the standard theory of scenario optimisation has related the risk of the data-based solution to the number of optimisation variables, a more recent approach, called the “wait-and-judge” scenario approach, enables the user to assess the risk of the solution in a data-dependent way, based on the number of decisive scenarios (“support scenarios”). The aim of this paper is to illustrate the potentials of the wait-and-judge approach for min–max sample-based design and we shall consider to this purpose an antenna array design problem.
File in questo prodotto:
File Dimensione Formato  
paper.pdf

embargo fino al 02/03/2020

Descrizione: Articolo nella versione accettata (non è versione finale)
Tipologia: Documento in Pre-print
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 449.84 kB
Formato Adobe PDF
449.84 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/513945
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 6
social impact