New algorithmic framework for conditional value at risk: Application to stochastic fixed-charge transportation
| Autor: | Yolanda Hinojosa, Francisco Saldanha-da-Gama, Justo Puerto, Elena Fernández |
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| Rok vydání: | 2019 |
| Předmět: |
Scheme (programming language)
Mathematical optimization Information Systems and Management General Computer Science Computer science Risk aversion Transportation theory Management Science and Operations Research Industrial and Manufacturing Engineering Expected shortfall Fixed charge Modeling and Simulation Focus (optics) Value (mathematics) computer computer.programming_language |
| Zdroj: | European Journal of Operational Research. 277:215-226 |
| ISSN: | 0377-2217 |
| DOI: | 10.1016/j.ejor.2019.02.010 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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