2 options
Hybrid offline/online methods for optimization under uncertainty / A. De Filippo.
- Format:
- Book
- Author/Creator:
- De Filippo, A., 1961- author.
- Series:
- Frontiers in artificial intelligence and applications ; Volume 349.
- Frontiers in Artificial Intelligence and Applications Series ; Volume 349
- Language:
- English
- Subjects (All):
- Mathematical optimization.
- Uncertainty (Information theory).
- Physical Description:
- 1 online resource (126 pages)
- Edition:
- First edition.
- Place of Publication:
- Amsterdam, Netherlands : IOS Press, [2022]
- Summary:
- Balancing the solution-quality/time trade-off and optimizing problems which feature offline and online phases can deliver significant improvements in efficiency and budget control.Offline/online integration yields benefits by achieving high quality solutions while reducing online computation time.
- Contents:
- 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
- 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
- Results for the VRP
- Trade-Offs of Online Anticipatory Algorithms
- Motivations of ``Taming" an Online Anticipatory Algorithm
- Offline Information Availability.
- 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
- The Models of Uncertainty
- Instantiating ANTICIPATE-D
- Instantiating CONTINGENCY
- Instantiating CONTINGENCY-D
- The Traveling Salesman Problem Case Study
- Results for the TSP
- Concluding Remarks &
- Future Works
- Bibliography.
- Notes:
- Includes bibliographical references.
- Description based on publisher supplied metadata and other sources.
- Description based on print version record.
- Other Format:
- Print version: De Filippo, A. Hybrid Offline/Online Methods for Optimization under Uncertainty
- ISBN:
- 9781643682631
- OCLC:
- 1317842369
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.