Simulated Annealing with estimated temperature

Temperature is the control parameter of Simulated Annealing, one of the bes t-known local search optimisation algorithms. Scheduling the temperature ev olution during optimisation is a crucial component of simulated annealing. We propose to elect acceptance probability as a new control parameter of si mulated annealing. The concept of imposing a schedule to acceptance probabi lity throughout optimisation yields a new algorithm. A general local search optimisation platform has been designed and implemented to evaluate this a lgorithm on various representative problems. An efficiency analysis method of stochastic algorithms is proposed to compare the performance of this alg orithm with other classical and state-of-the-art algorithms. Beyond excelle nt performance, our algorithm demonstrates the advantage of the new exploit of acceptance probability. This concept can also be applied to other stoch astic algorithms such as Evolutionary Algorithms.