Simulated annealing is a numerical optimization technique. The Lam-Delosme annealing schedule provides a particularly efficient method of performing this process. More information about Lam-Delosme is available here.

Source code implementing parallelized Lam-Delosme simulated annealing within Mathematica is available here. An example which optimizes the parameters for a simple xCellerator model is here.

References:
King-Wai Chu, Yuefan Deng, and John Reinitz, "Parallel Simulated Annealing by Mixing of States," Journal of Computational Physics, 148, 1999. (pdf)

Johannes Jaeger et. al., "Dynamic control of positional information in the early Drosophila embryo," Nature, 430, 2004. (pdf)

Jimmy Lam, "An Efficient Simulated Annealing Schedule," Technical Report 8818, Ph.D. Dissertation, Yale Electrical Engineering Department, New Haven, CT, September 1988. (pdf)

Jimmy Lam and Jean-Marc Delosme, "An Efficient Simulated Annealing Schedule: Derivation," Technical Report 8816, Yale Electrical Engineering Department, New Haven, CT, September 1988. (pdf)

Jimmy Lam and Jean-Marc Delosme, "An Efficient Simulated Annealing Schedule: Implementation and Evaluation," Technical Report 8817, Yale Electrical Engineering Department, New Haven, CT, September 1988. (pdf)

John Reinitz and David H. Sharp, "Mechanism of eve stripe formation," Mechanisms of Development, 49, 1995. (pubmed)