本段落提供了一种基于自适应机制改进的经典模拟退火算法的完整源代码。该代码优化了解决组合优化问题的能力,并提高了搜索效率和解的质量。
Adaptive Simulated Annealing (ASA) is a C-language program designed to find the optimal global fit for a nonlinear, non-convex cost function in a D-dimensional space. This algorithm includes an annealing schedule where temperature T decreases exponentially with respect to annealing time k as follows: \(T = T_0 \exp(-c k^{1/D})\). The introduction of re-annealing allows the program to adjust sensitivities across different dimensions within the parameter space effectively. ASAs cooling schedule is faster than fast Cauchy annealing, where temperature decreases linearly with time (\(T = T_0 / k\)), and much quicker than Boltzmann annealing, which follows a logarithmic decrease in temperature over time (\(T = T_0 / \ln(k)\)). ASA offers more than 100 OPTIONS to finely tune the algorithm for various classes of nonlinear stochastic systems.