# Stochastic Optimization and Reinforcement Learning for the Resilience of Infrastructure Networks against Climate Change

Pascal Quach, Yiping Fang, Anne Barros

► To cite this version:

Pascal Quach, Yiping Fang, Anne Barros. Stochastic Optimization and Reinforcement Learning for the Resilience of Infrastructure Networks against Climate Change. Journée de l'ED INTERFACES 2023-2024, Mar 2024, Gif-sur-Yvette, France. hal-05008991

HAL Id: hal-05008991

https://hal.science/hal-05008991v1

Submitted on 3 Apr 2025

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Distributed under a Creative Commons Attribution 4.0 International License
## Applications

### (O-I-II) – Pre-event network hardening, risk identification/assessment/mitigation, impact reduction, resilience enhancement

### (2024) Resilience enhancement of distributions networks with robust optimal sizing and location under uncertainty and random contingencies

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### (II-III-IV) – Post-event information gathering, damage assessment, resources allocation, relief logistics, repair crew dispatch, service restoration, system recovery, etc.

## Context

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Essential services

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Increased frequency and/or intensity of weather and climate extremes **(High-Impact Low-Probability)**

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Aging infrastructure and interdependencies

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Directive (EU) 2022/2557 & French National Resilience Strategy

## Methodology

(Ex ante)

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planning and mitigation

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I) Targets: risk reduction and increased resilience

II) Challenges: deep uncertainty of failure scenarios

III) Techniques: stochastic, (distributionally) robust optimization, robust satisfying

(Ex post)

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response and service restoration

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I) Targets: survivability and rapid recovery

II) Challenges: time constraints vs computational complexity

III) Techniques: deep reinforcement learning

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## Resilience is a multi-temporal concept

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## Outcomes

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### A. Knowledge consolidation:

1. Ex ante resilience enhancements actions

2. Natural hazards targeting critical infrastructures

3. National and European strategies for resilience

4. Methodological tools

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### B. Optimization models

1. Baseline optimization models for system operations, failures, and resilience actions

2. Development of robust counterparts under deep uncertainty of future disruptions

3. Ex post problems formulation

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### C. Case studies

1. Ex ante resilience enhancement on power distribution networks

2. Ex post response and recovery problems for disaster management

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### D. Scientific Production

1. Workshops & Conferences

a. SESO, WISG, etc.

b. ESREL, EURO, etc.

2. Journal publications

3. Thesis

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### References

Start of thesis

A.1-2

B.1 A.3-4

B.2 C.1

C.1 B.3

C.1 C.2

D.2-3 Thesis defence

February 2023

August 2023

February 2024

August 2024

February 2025

August 2025

February 2026

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