An overview of physical annealing and simulated annealing methods is presented. The target audience includes computational analysts and software engineers who are considering simulated annealing for the solution of a combinatorical optimization problem. Several important implementation issues are discussed including decompositions for parallel programming. Special emphasis is given to the often...

Simulated annealing is a well-studied local search metaheuristic used to address discrete and, to a lesser extent, continuous optimization problems. The key feature of simulated annealing is that it provides a mechanism to escape local optima by allowing hill-climbing moves (i.e., moves which worsen the objective function value) in hopes of finding a global optimum. A brief history of simulated...

The simulated annealing algorithm has been introduced into the broadcast routing of wireless sensor network so as to reduce the length and energy of broadcast path. However, its new solution is generated by randomly exchanging the location of two sensor nodes of broadcast path. Though the simulated annealing algorithm is better than 2-opt algorithm, its method of generating new solution has sti...

We consider in this paper the uplink slot assignment problem in a multi-spot geostationary satellite. Radio interference impose constraints on the slots that can simultaneously be assigned in different cells that have the same frequency. The problem is shown to be an NP-complete one, which motivates us to search for a heuristic solution approach. We describe here a heuristic solution based on s...

in this study, the effects of nitrogen addition on the production of ultrafine/nano grained aisi 201l stainlesssteel by advanced thermo-mechanical process were investigated. cast samples were first homogenized at 1200 °c for 4 h, hot-rolled at 1100 °c and finally, solution-annealed at 1150 °c for 2.5 h. unidirectional and cross multipass cold rolling at 25 °c was carried out to 90% reduction in...

The semi-supervised support vector machine (SVM) is a maximum-margin classification algorithm based on both labeled and unlabeled data. Training SVM involves either a combinatorial or non-convex optimization problem and thus finding the global optimal solution is intractable in practice. It has been demonstrated that a key to successfully find a good (local) solution of SVM is to gradually incr...

The simulated annealing (SA) algorithm [14] [5] has been applied to every di cult optimization problem in VLSI CAD. Existing SA implementations use monotone decreasing, or cooling, temperature schedules motivated by the algorithm's proof of optimality as well as by an analogy with statistical thermodynamics. This paper gives strong evidence that challenges the correctness of using such schedule...

Planar superstrate CuInS2 (CIS) solar cell devices are fabricated using totally solution-processed deposition methods. A titanium dioxide blocking layer and an In2S3 buffer layer are deposited by the spray pyrolysis method. A CIS2 absorber layer is deposited by the spin coating method using CIS ink prepared by a 1-butylamine solvent-based solution at room temperature. To obtain optimum annealin...

Floorplanning is an essential step in physical design of VLSI. The floorplan design problem is how to place a set of circuit modules on a chip such that the resulting area is minimized. The best known solutions are obtained using simulated annealing based on sequence pairs representing the planning of modules. The conventional simulated annealing algorithm conducts a random perturbation operati...