Author
Abstract
Simulated annealing (SA) has been considered as a good tool for search
and optimization problems which represent the abstraction of obtaining the
crystalline structure through a physical process. This algorithm works sequentially
that the current state will produce only one next state. That will make the search to
be slower and the important drawback is that the search may fall in local minimum
which represent the best solution in only part of the solution space. In this work
we present the transformation of Simulated Annealing algorithm into quantum
version which will be called Quantum Simulated Annealing (QSA). This
algorithm will overcome the drawbacks of slowness and local minimum falling by
produce as much as possible of the neighbor states and work on in parallel by
exploiting the massive parallelism feature in quantum computation. The results
show that QSA can find the optimal path in smaller number of iterations than the
sequential simulated annealing algorithm and the time complexity of QSA is
better than any other parallel simulated annealing algorithm.
Keywords
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