Abstract

Neighbourhood structure and size are important parameters in local search algorithms. This is also true for generalised local search algorithms like simulated annealing. It has been shown that the performance of simulated annealing can be improved by adopting a suitable neighbourhood size. However, previous studies usually assumed that the neighbourhood size was fixed during search. This paper presents a simulated annealing algorithm with a dynamic neighbourhood size which depends on the current "temperature" value during search. A method of dynamically deciding the neighbourhood size by approximating a continuous probability distribution is given. Four continuous probability distributions are used in our experiments to generate neighbourhood sizes dynamically, and the results are compared. 1 Introduction Simulated Annealing (SA) algorithms can find very good near optimal solutions to a wide range of hard problems, but at the high computational cost. Various methods have been proposed...

Citations

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