Artículo
New algorithmic framework for conditional value at risk: Application to stochastic fixed-charge transportation
Autor/es | Fernández, Elena
Hinojosa Bergillos, Yolanda Puerto Albandoz, Justo Saldanha da Gama, Francisco |
Departamento | Universidad de Sevilla. Departamento de Economía Aplicada I Universidad de Sevilla. Departamento de Estadística e Investigación Operativa |
Fecha de publicación | 2019-08 |
Fecha de depósito | 2024-02-05 |
Publicado en |
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Resumen | This paper introduces a new algorithmic scheme for two-stage stochastic mixed-integer programming assuming a risk averse decision maker. The focus is the minimization of the conditional value at risk for a hard combinatorial ... This paper introduces a new algorithmic scheme for two-stage stochastic mixed-integer programming assuming a risk averse decision maker. The focus is the minimization of the conditional value at risk for a hard combinatorial optimization problem. Some properties of a mixed-integer non-linear programming formulation for conditional value at risk are studied as well as their algorithmic implications. This yields to a procedure for obtaining lower and upper bounds on the optimal value of the problem that may lead to an optimal solution. The new developments are applied to a fixed-charge transportation problem with stochastic demand, and they are computationally tested. The corresponding results are thoroughly presented and discussed. |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España Fundação para a Ciência e Tecnologia (Portugal) |
Identificador del proyecto | MTM2015-63779-R
MTM2016-74983-C02-01 UID/MAT/04561/2013 |
Cita | Fernández, E., Hinojosa Bergillos, Y., Puerto Albandoz, J. y Saldanha da Gama, F. (2019). New algorithmic framework for conditional value at risk: Application to stochastic fixed-charge transportation. European Journal of Operational Research, 277 (1), 215-226. https://doi.org/10.1016/j.ejor.2019.02.010. |
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