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Simheuristics

Simheuristics is a hybrid algorithmic framework that integrates Monte Carlo or discrete-event simulation into metaheuristic search procedures to solve stochastic combinatorial optimization problems. Introduced by Juan et al. in 2015, it addresses settings where objective function evaluations involve random variables, providing near-optimal solutions with probabilistic quality guarantees. The approach is especially suited for real-world logistics, transportation, and scheduling problems where uncertainty is inherent and classical deterministic solvers fail to capture variability.

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Simheuristics (Simulation + Metaheuristics)

Taxonomisk metodpost · process-pipeline / optimization

Juan, A. A., et al. (2015). A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems. Operations Research Perspectives, 2, 62–72. · DOI 10.1016/j.orp.2015.03.001

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Same method familyDiscrete-Event Simulationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMatheuristicsmachine-suggested · Relational suggestion, not evidence.Same method familyStochastic Optimizationmachine-suggested · Relational suggestion, not evidence.