ERC-2022-ADG: "DECIDE - Machine learning for decision making under uncertainty"

Project Details

Description

HORIZON-ERC, project 101093188

Layman's description

Many important decisions are taken under uncertainty since we do not know the development of various parameters. In particular the ongoing green transition requires large and urgent societal investments in new energy modes, infrastructure and technology. The decisions are spanning over a very long time-horizon, and there are large uncertainty towards energy prices, demand of energy, and production from renewable sources. Such problem can be described as
two-stage stochastic optimization problems, where we first decide which facilities to establish, and then we have to schedule the production/transportation for a stochastic demand, using the given facilities. If the decision variables are
binary (e.g. location of facilities) such problems are extremely difficult to solve. In this project we will develop a new framework for investment decision making under uncertainty based on a combination of machine learning and operations research. Instead of solving a complex stochastic optimization problem defined on a fixed set of forecasted scenarios, we propose to use an iterative process: We will repeatedly generate new scenarios, solve them using advanced optimization methods, and find the corresponding investment solutions. Our novel way of optimization will
use generative adversarial networks (GANs) to generate scenarios in order to find still better approximations of the real problem, while also diversifying the search so that we uncover the full solution space. The outcome of the iterative process is a palette of near-optimal solutions, which can be analyzed using data science methods to extract robust solutions and outrank dominated choices. Knowing the full spectrum of possible choices opens up for a much broader discussion of investments, while allowing soft constraints to also be taken into account. This will enable a more transparent and inclusive decision process, while ensuring well-founded and more robust investment decisions.
Short titleMachine learning for decision making under uncertainty
AcronymDECIDE
StatusActive
Effective start/end date01/01/202431/12/2029

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 7 - Affordable and Clean Energy
  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action

Keywords

  • Optimization; Algorithms; Machine Learning;

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