Modern optimization methods for decision making under risk and uncertainty / edited by Alexei A. Gaivoronski, Pavel S. Knopov and Volodymyr A. Zaslavskyi
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TextPublication details: Boca Raton : CRC Press, 2024Description: viii, 380 pISBN: - 9781032196435
- 519.6 MOD-
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| Current library | Call number | Status | Barcode | |
|---|---|---|---|---|
| UMT Main Campus | 519.6 MOD- (Browse shelf(Opens below)) | Available | 153340 |
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| 519.6 DOR-A Ant colony optimization | 519.6 GOR-O Optimization and control of dynamic systems : | 519.6 KAM-D Dynamic optimization : the calculus of variations and optical control in economics and management/ | 519.6 MOD- Modern optimization methods for decision making under risk and uncertainty / | 519.602462 BEL-O Optimization concepts and applications in engineering | 519.602855133 POS-H Hands-on mathematical optimization with Python / | 519.64 HAN- Handbook of ant colony : |
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"Uncertainties, risks, and disequilibria are pervasive characteristics of modern socio-economic, technological, and environmental systems involving interactions among various factors in economy, technology and nature. The systems are characterized by interdependencies, discontinuities, endogenous risks and thresholds, requiring non-smooth quantile-based performance indicators, goals and constraints for their explaining and planning. The two-stage stochastic optimization with stochastic quasi-gradients enables designing a robust portfolio of interdependent precautionary strategic and adaptive operational decisions making the systems resilient with respect to potential uncertainties and risks"-- Provided by publisher
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