Process / pipelineSimulation / optimization
Deterministic Simulated Annealing — Annealing-schedule optimization without stochastic acceptance
Deterministic Simulated Annealing (DSA) is an optimization metaheuristic that adopts the cooling-schedule structure of classical simulated annealing but replaces the probabilistic Metropolis acceptance criterion with a strictly deterministic rule: only improving moves are accepted. This yields a reproducible, greedy-descent procedure guided by an annealing temperature schedule.
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Sources
- Rose, K., Gurewitz, E., Fox, G. C. (1990). A deterministic annealing approach to clustering. Pattern Recognition Letters, 11(9), 589-594. DOI: 10.1016/0167-8655(90)90010-Y ↗
- 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 ↗