Risk optimization with p-order conic constraints: A linear programming approach |
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Authors: | Pavlo A Krokhmal Policarpio Soberanis |
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Institution: | Department of Mechanical and Industrial Engineering, The University of Iowa, 3131 Seamans Center, Iowa City, IA 52242, USA |
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Abstract: | The paper considers solving of linear programming problems with p-order conic constraints that are related to a certain class of stochastic optimization models with risk objective or constraints. The proposed approach is based on construction of polyhedral approximations for p-order cones, and then invoking a Benders decomposition scheme that allows for efficient solving of the approximating problems. The conducted case study of portfolio optimization with p-order conic constraints demonstrates that the developed computational techniques compare favorably against a number of benchmark methods, including second-order conic programming methods. |
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Keywords: | p-order conic programming Second-order conic programming Polyhedral approximation Risk measures Stochastic programming Portfolio optimization |
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