In this paper we consider the control of a complex network of servers through which many types of jobs flow, where we assume that servers require a setup time when changing between types. Such networks can be used to model complex communication, traffic or manufacturing systems. Instead of...

We study generalizations of parallel tempering, also known as replica exchange method, that aim at maximizing the sampling of independent low energy configurations through enforcing random walks in temperature (or other control variables). The advantage of these techniques is the easily tunable...

A new method for the combinatorial optimization of quasi-one-dimensional systems is presented. This method is in close analogy with the well-known transfer-matrix method. The method allows for the calculation of the lowest energy levels of the system. However, when finding the ground and some...

The minimum spanning trees on scale-free graphs are shown to be scale-free as well, in the presence of random edge weights. The probability distribution of the weights on the tree differs from regular lattices reflecting the typically short distances (small-world property). We consider also the...

We consider the applicability of stochastic global optimization algorithms on test-functions whose domain of definition is a simply-connected and finite interval of real numbers. We argue on the basis of theoretical reflections of statistical physics (namely random-walk) and computer simulations...

Global optimization (GO) is one of the key numerical tools in computational physics. Among the GO algorithms the ones originating in statistical physics are particularly powerful. Recently an adaptive scheme was developed to increase the efficiency of one of these algorithms (stochastic...

Using a simple, annealed model, some of the key features of the recently introduced extremal optimization heuristic are demonstrated. In particular, it is shown that the dynamics of local search possesses a generic critical point under the variation of its sole parameter, separating phases of...

Typical combinatorial optimizations are NP-hard; however, for a particular class of cost functions the corresponding combinatorial optimizations can be solved in polynomial time using the transfer matrix technique or, equivalently, the dynamic programming approach. This suggests a way to...