Simulated Jumping

This paper describes a novel approach for solving combinatorial optimisation problems called Simulated Jumping. It is based on ideas from spin-glasses, simulated annealing and self-organisation. We start from a low temperature, and the system is then subjected to a rapid heating and cooling process (a shaking process). This process is controlled by the system's energy in a self-organised manner. The heating and cooling process will continuously melt and freeze local regions: this process pushes the system out of local minima and hence minimises the energy function. Application of the Simulated Jumping method to the Quadratic Assignment and Asymmetric Travelling Salesman problems gives promising results.