Process / pipelineSimulation / optimization

Robust Simulated Annealing — Finding solutions that stay good under uncertainty

Robust Simulated Annealing (RSA) adapts the classical simulated annealing metaheuristic to seek solutions that perform well not just under nominal conditions but across the full range of uncertain or adversarial parameter values. By embedding a robustness evaluation — worst-case, expected-case, or regret-based — into the SA acceptance step, RSA trades some nominal optimality for resilience, making it valuable when problem parameters are imprecisely known or subject to environmental variation.

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Sources

  1. Kirkpatrick, S., Gelatt, C. D., Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671-680. DOI: 10.1126/science.220.4598.671
  2. Ben-Tal, A., El Ghaoui, L., Nemirovski, A. (2009). Robust Optimization. Princeton University Press, Princeton, NJ. ISBN: 9780691143682

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Referenced by

ScholarGateRobust Simulated Annealing (Robust Simulated Annealing — Uncertainty-aware stochastic local search for robust solutions). Retrieved 2026-06-04 from https://scholargate.app/en/simulation/robust-simulated-annealing