Hybrid method for a class of stochastic bi-criteria optimization problems.
Wan, Zhong, Hao, Aiyun, Meng, Fuzheng, Hu, Chaoming (2010)
Journal of Inequalities and Applications [electronic only]
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Wan, Zhong, Hao, Aiyun, Meng, Fuzheng, Hu, Chaoming (2010)
Journal of Inequalities and Applications [electronic only]
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Jitka Dupačová (2010)
Kybernetika
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In applications of geometric programming, some coefficients and/or exponents may not be precisely known. Stochastic geometric programming can be used to deal with such situations. In this paper, we shall indicate which stochastic programming approaches and which structural and distributional assumptions do not destroy the favorable structure of geometric programs. The already recognized possibilities are extended for a tracking model and stochastic sensitivity analysis is presented in...
Pham, Huyên (2005)
Probability Surveys [electronic only]
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Dias, Bruno H., Marcato, André L.M., Souza, Reinaldo C., Soares, Murilo P., Junior, Ivo C.Silva, de Oliveira, Edimar J., Brandi, Rafael B.S., Ramos, Tales P. (2010)
Mathematical Problems in Engineering
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Stefan M. Stefanov (2000)
The Yugoslav Journal of Operations Research
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Huang, Zongyuan, Wu, Zhen (2010)
Mathematical Problems in Engineering
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Tomáš Rusý, Miloš Kopa (2018)
Kybernetika
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We build a multi-stage stochastic program of an asset-liability management problem of a leasing company, analyse model results and present a stress-testing methodology suited for financial applications. At the beginning, the business model of such a company is formulated. We introduce three various risk constraints, namely the chance constraint, the Value-at-Risk constraint and the conditional Value-at-Risk constraint along with the second-order stochastic dominance constraint, which...
Jianhui Huang, Jingtao Shi (2012)
ESAIM: Control, Optimisation and Calculus of Variations
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This paper deals with the optimal control problem in which the controlled system is described by a fully coupled anticipated forward-backward stochastic differential delayed equation. The maximum principle for this problem is obtained under the assumption that the diffusion coefficient does not contain the control variables and the control domain is not necessarily convex. Both the necessary and sufficient conditions of optimality are proved. As illustrating examples, two kinds of linear...
Stefan Ankirchner, Thomas Kruse (2015)
Banach Center Publications
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We consider the dynamic control problem of attaining a target position at a finite time T, while minimizing a linear-quadratic cost functional depending on the position and speed. We assume that the coefficients of the linear-quadratic cost functional are stochastic processes adapted to a Brownian filtration. We provide a probabilistic solution in terms of two coupled backward stochastic differential equations possessing a singularity at the terminal time T. We verify optimality of the...
Łukasz Delong (2005)
Applicationes Mathematicae
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The aim of this paper is to construct an optimal investment strategy for a non-life insurance business. We consider an insurance company which provides, in exchange for a single premium, full coverage to a portfolio of risks which generates losses according to a compound Poisson process. The insurer invests the premium and trades continuously on the financial market which consists of one risk-free asset and n risky assets (Black-Scholes market). We deal with the insurer's wealth path...