Name
Abstract | ||
|---|---|---|
In earlier proposals, the robust counterpart of conic optimization problems exhibits a lateral increase in complexity, i.e., robust linear programming problems (LPs) become second order cone problems (SOCPs), robust SOCPs become semidefinite programming problems (SDPs), and robust SDPs become NP-hard. We propose a relaxed robust counterpart for general conic optimization problems that (a) preserves the computational tractability of the nominal problem; specifically the robust conic optimization problem retains its original structure, i.e., robust LPs remain LPs, robust SOCPs remain SOCPs and robust SDPs remain SDPs, and (b) allows us to provide a guarantee on the probability that the robust solution is feasible when the uncertain coefficients obey independent and identically distributed normal distributions. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/s10107-005-0677-1 | Math. Program. |
Keywords | Field | DocType |
stochastic optimization,robust solution,conic optimization problem,general conic optimization problem,tractable approximations,robust optimization,conic optimization,robust sdps,robust counterpart,robust socps,robust linear programming problem,robust lps,robust conic optimization problem,robust conic optimization problems,nominal problem,independent and identically distributed,normal distribution,linear program | Normal distribution,Mathematical optimization,Stochastic optimization,Robust optimization,Independent and identically distributed random variables,Linear programming,Conic programming,Conic optimization,Semidefinite programming,Mathematics | Journal |
Volume | Issue | ISSN |
107 | 1 | 1436-4646 |
Citations | PageRank | References |
93 | 6.17 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dimitris J. Bertsimas | 1 | 4513 | 365.31 |
| Melvyn Sim | 2 | 1909 | 117.68 |