Simulated annealing, its parameter settings and the longest common subsequence problem

Abstract

Simulated Annealing is a probabilistic search heuristic for solving optimization problems and is used with great success on real life problems. In its standard form Simulated Annealing has two parameters, namely the initial temperature and the cooldown factor. In literature there are only rules of the thumb for choosing appropriate parameter values. This paper investigates the influence of different values for these two parameters on the optimization process from a theoretical point of view and presents some criteria for problem specific adjusting of these parameters.