Hybrid Offline/Online Methods for Optimization under Uncertainty.

Hybrid Offline/Online Methods for Optimization under Uncertainty.

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Bibliographic Details
Superior document:Frontiers in Artificial Intelligence and Applications Series ; v.349
:
De Filippo, A.
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
Online Access:
Physical Description:1 online resource (126 pages)
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Table of 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
  • 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.
  • 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 &amp
  • Future Works
  • Bibliography.

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