An algorithm is developed to statistically find the best global fit of a nonlinear non-convex cost-function over a D-dimensional space. It is argued that this algorithm permits an annealing schedule for ''temperature'' T decreasing exponentially in annealing-time k, T = T 0 exp(−ck 1/D). The introduction of re-annealing also permits adaptation to changing sensitivities in the multi-dimensional ...

We propose a new stochastic algorithm (generalized simulated annealing) for computationally finding the global minimum of a given (not necessarily convex) energy/cost function defined in a continuous D-dimensional space. This algorithm recovers, as particular cases, the so called classical (“Boltzmann machine”) and fast (“Cauchy machine”) simulated annealings, and can be quicker than both. Key-...

We applied simulated annealing algorithm to nurse scheduling problem. For time complexity problem of simulated annealing, we suggested an efficient transition rule using cost matrix for simulated annealing. The experimental results showed that the suggested method generated a nurse scheduling faster in time and better in quality compared to traditional simulated annealing.

Simulated annealing is known to be an efficient method for combinatorial optimization problems. Its usage for real-life problems has been limited by the long execution time. This report presents a new approach to asynchronous simulated annealing for parallel thread oriented multiprocessor operating systems. Experimental results of the 100to 1000-city traveling salesman problems on the two-proce...

n different nodes of the network. The two algorithms have been applied to the job shop scheduling problem (JSS) and the traveling salesman problem (TSP). Both algorithms showed very good performance in terms of solution time and solution quality. The rest of the paper is organized in the following fashion. Section II describes the simulated annealing technique. Section III presents the cluster ...

Received on:2/6/2009 Accepted on:1/4/2010 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 dr...

Beginning in 1983, simulated annealing was marketed as a global optimization methodology that mimics the physical annealing process by which molten substances cool to crystalline lattices of minimal energy. This marketing strategy had a polarizing effect, attracting those who delighted in metaphor and alienating others who found metaphor insufficient at best and facile at worst. In fact, the em...

This paper presents a fast simulated annealing framework for combining multiple clusterings (i.e. clustering ensemble) based on some measures of agreement between partitions, which are originally used to compare two clusterings (the obtained clustering vs. a ground truth clustering) for the evaluation of a clustering algorithm. Though we can follow a greedy strategy to optimize these measures a...

Scheduling jobs on computational grids is a compute intensive problem. Existing methods are unable to perform the required breakthrough in terms of time and cost. A Grid scheduler must use the available resources efficiently, while satisfying competing and mutually conflicting goals. The grid workload may consist of multiple jobs, with varying resource requirements and quality-of-service constr...