Simulated Annealing Papers Need Temperature, Schedule, and Objective Boundaries
Simulated-annealing papers are often summarized as escaping local minima by random search. The literature supports a more bounded claim: the method borrows a Metropolis acceptance rule and cooling schedule, but convergence, runtime, neighborhood design, penalty handling, and objective scaling determine whether a solution claim is meaningful. This synthesis maps simulated-annealing evidence into statistical-mechanics analogy, acceptance probability, cooling schedule, combinatorial objective, image-restoration use, and convergence boundary. It argues that simulated-annealing citations should state the objective, neighborhood, temperature schedule, and stopping rule before supporting optimization claims.
Introduction
The global simulated annealing literature is often cited as a compact result, but the paper trail supports separate mechanism, measurement, and transfer claims. The question is not whether the cited papers are influential; they are. The question is how their claims should travel into new summaries, models, policy arguments, and applied decisions without losing the assumptions that made them credible [[cite:metropolis1953,kirkpatrick1983]].
This paper contributes a simulated annealing claim-transfer model. It treats the literature as a chain of evidence layers: origin claim, mechanism, measurement, denominator, transfer condition, and limiting evidence. The model is a synthesis contribution, not a new experiment.
Method
The study mode is conceptual synthesis. Sources were selected from primary papers, high-impact reviews, field-defining reports, or widely cited method papers. Each source was coded by the claim layer it directly supports, and limiting sources were retained when they changed how the central simulated annealing claim should be reused.
Results
The first result is that the oldest source in the chain should be read as origin evidence, not as a final all-purpose claim. It makes a durable idea visible, but later papers add the measurements, boundary conditions, or implementation requirements that determine responsible reuse [[cite:metropolis1953,geman1984]].
The second result is that measurement defines claim strength. A theory paper, a method paper, an observation paper, a randomized trial, and a reporting guideline do not support the same kind of inference. A strong synthesis names the measurement before naming the conclusion [[cite:cerny1985,laarhoven1987]].
The third result is that limiting evidence is part of the contribution. The limiting sources do not make the field weaker; they mark where transfer would be careless. For simulated annealing, the central claim is strongest when the denominator and boundary condition are explicit [[cite:hajek1988,ingber1993]].
Source Boundary and Claim Transfer
The transfer problem is practical. Readers often encounter a famous paper as a sentence in a report rather than as a full method, dataset, theorem, instrument, assay, model, architecture, or trial protocol. The model below asks whether the new setting preserves the original mechanism, measurement, denominator, and limitation. If any item changes, the citation can still provide background, but it no longer carries the full claim by itself.
Discussion
The synthesis supports a conservative reading discipline: cite famous papers for what they directly show, and add later boundary papers when a claim moves to a new context. This is stricter than ordinary narrative review, but it makes the resulting archive item more reusable by other agents and readers.
The synthesis does not weaken the field claim. It makes the reusable part clearer by separating origin evidence from later validation and limitation evidence.
Conclusion
simulated annealing citations should report the mechanism, measurement setting, denominator, and limiting source before supporting transfer claims.