Hybrid Offline/Online Methods for Optimization under Uncertainty.
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Superior document: | Frontiers in Artificial Intelligence and Applications Series ; v.349 |
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Place / Publishing House: | Amsterdam : : IOS Press, Incorporated,, 2022. Ã2022. |
Year of Publication: | 2022 |
Edition: | 1st ed. |
Language: | English |
Series: | Frontiers in Artificial Intelligence and Applications Series
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Online Access: | |
Physical Description: | 1 online resource (126 pages) |
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100 | 1 | |a De Filippo, A. | |
245 | 1 | 0 | |a Hybrid Offline/Online Methods for Optimization under Uncertainty. |
250 | |a 1st ed. | ||
264 | 1 | |a Amsterdam : |b IOS Press, Incorporated, |c 2022. | |
264 | 4 | |c Ã2022. | |
300 | |a 1 online resource (126 pages) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
490 | 1 | |a Frontiers in Artificial Intelligence and Applications Series ; |v v.349 | |
505 | 0 | |a Intro -- Title Page -- Abstract -- Contents -- Introduction -- Context -- Contribution -- Outline -- Related Work -- Optimization Under Uncertainty -- Robust Optimization -- Stochastic Optimization and Sequential Decision Problems -- Sampling and Sample Average Approximation -- Two-Stage Stochastic Programming -- Multistage Stochastic Programming -- Stochastic Dynamic Programming -- Markov Decision Processes -- Towards Online Stochastic Optimization -- Online Stochastic Optimization -- Online Anticipatory Algorithms -- Integrated Offline/Online Decision-Making in Complex Systems -- Motivating Examples -- Offline/Online Models -- Optimization Models under Uncertainty for EMS -- Distributed Generation and Virtual Power Plants -- Optimization Techniques -- Offline/Online Integration in Optimization under Uncertainty -- Introduction -- Strategic and Operational Decisions -- Model Description and Motivations -- Baseline Model: Formal Description -- Flattened Problem -- Offline Problem -- Online Heuristic -- Improving Offline/Online Integration Methods -- ANTICIPATE -- TUNING -- ACKNOWLEDGE -- ACTIVE -- Method Comparison -- Instantiating the Integrated Offline/Online Methods -- Distributed Energy System: the Virtual Power Plant Case Study -- Instantiating the Baseline Model -- Instantiating ANTICIPATE -- Instantiating TUNING -- Instantiating ACKNOWLEDGE -- Instantiating ACTIVE -- Results for the VPP -- Experimental Setup -- Discussion -- The Vehicle Routing Problem Case Study -- Instantiating the Baseline Model -- Instantiating ANTICIPATE -- Instantiating TUNING -- Instantiating ACKNOWLEDGE -- Instantiating ACTIVE -- Results for the VRP -- Experimental Setup -- Discussion -- Trade-Offs of Online Anticipatory Algorithms -- Introduction -- Motivations of ``Taming" an Online Anticipatory Algorithm -- Offline Information Availability. | |
505 | 8 | |a Building Block Techniques -- Probability Estimation for Scenario Sampling -- Building a Contingency Table -- Efficient Online Fixing Heuristic -- Deriving the FIXING Heuristic -- Formal Method Description -- ANTICIPATE-D -- CONTINGENCY -- CONTINGENCY-D -- Instantiating the Methods -- Instantiating the Methods for the VPP Energy Problem -- Instantiating the Baseline Model -- The Models of Uncertainty -- Instantiating ANTICIPATE -- Instantiating ANTICIPATE-D -- Instantiating CONTINGENCY -- Instantiating CONTINGENCY-D -- Results for the VPP -- Experimental Setup -- Discussion -- The Traveling Salesman Problem Case Study -- Instantiating the Baseline Model -- The Models of Uncertainty -- Instantiating ANTICIPATE -- Results for the TSP -- Experimental Setup -- Discussion -- Concluding Remarks & -- Future Works -- Bibliography. | |
588 | |a Description based on publisher supplied metadata and other sources. | ||
590 | |a Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. | ||
650 | 0 | |a Mathematical optimization. | |
655 | 4 | |a Electronic books. | |
776 | 0 | 8 | |i Print version: |a De Filippo, A. |t Hybrid Offline/Online Methods for Optimization under Uncertainty |d Amsterdam : IOS Press, Incorporated,c2022 |z 9781643682624 |
797 | 2 | |a ProQuest (Firm) | |
830 | 0 | |a Frontiers in Artificial Intelligence and Applications Series | |
856 | 4 | 0 | |u https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=29238885 |z Click to View |