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Communication Dans Un Congrès Année : 2022

Hybrid Acquisition Processes in Surrogate-based Optimization. Application to Covid-19 Contact Reduction

Résumé

Parallel Surrogate-Assisted Evolutionary Algorithms (P-SAEAs) are based on surrogate-informed reproduction operators to propose new candidates to solve computationally expensive optimization problems. Differently, Parallel Surrogate-Driven Algorithms (P-SDAs) rely on the optimization of a surrogate-informed metric of promisingness to acquire new solutions. The former are promoted to deal with moderately computationally expensive problems while the latter are put forward on very costly problems. This paper investigates the design of hybrid strategies combining the acquisition processes of both P-SAEAs and P-SDAs to retain the best of both categories of methods. The objective is to reach robustness with respect to the computational budgets and parallel scalability.
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Dates et versions

hal-03770742 , version 1 (06-09-2022)

Identifiants

  • HAL Id : hal-03770742 , version 1

Citer

Guillaume Briffoteaux, Nouredine Melab, Mohand Mezmaz, Daniel Tuyttens. Hybrid Acquisition Processes in Surrogate-based Optimization. Application to Covid-19 Contact Reduction. BIOMA 2022 - International Conference on Bioinspired Optimisation Methods and Their Applications, Nov 2022, Maribor, Slovenia. ⟨hal-03770742⟩
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