This paper discusses design and comparison of Simulated Annealing Algorithm and Greedy Randomized Adaptive Search Procedure (GRASP) to minimize the makespan in scheduling n single operation independent jobs on m unrelated parallel machines. This problem of minimizing the makespan in single machine scheduling problem with uniform parallel machines is NP hard. Hence, heuristic development for suc...

Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a compute-intensive process, and as a result several research efforts have been undertaken to parallelize this algorithm. Most previous parallel approaches to cell placement annealing have used a parallel moves approach. In this paper we investigate two new approaches that have been proposed for gen...

In this work, we propose a Hybrid particle swarm optimization-Simulated annealing algorithm and present a comparison with i) Simulated annealing algorithm and ii) Back propagation algorithm for training neural networks. These neural networks were then tested on a classification task. In particle swarm optimization behaviour of a particle is influenced by the experiential knowledge of the partic...

Simulated annealing is an established method for global optimization. Perhaps its most salient feature is the statistical promise to deliver a globally optimal solution. In this work, we propose a technique which attempts to combine the robustness of annealing in rugged terrain with the efficiency of local optimization methods in simple search spaces. On a variety of benchmark functions, the pr...

The layout design problem is a kind of nesting problems that is naturally NP-hard and very difficult to solve. Layout designing of machine is even more difficult because of its nesting items are actually machine parts that have both irregular shapes and complex constraints. A feasible way to solve machine layout problem is to employ ameliorative algorithms, such as simulated annealing algorithm...

Reducing synchronization constraints in parallel simulated annealing algorithms can improve performance. However, this introduces error in the global cost function. Previous work in parallel simulated annealing suggests that if the amount of error in the cost function is controlled, good quality results can still be obtained. In this paper, we present a model of error in asynchronous parallel s...

Boltzmann evolutionary algorithms and their embedded selection mechanisms are traditionally employed to prolong search. After a brief introduction, a precursor called simulated annealing is outlined. A prominent type of Boltzmann evolutionary algorithm called parallel recombinative simulated annealing is then covered in depth. A proof of global convergence for this type of algorithm is illustra...

mutual information (mi) is a widely used similarity metric for multimodality image registration. however, it involves an extremely high computational time especially when it is applied to volume images. moreover, its robustness is affected by existence of local maxima. the multi-resolution pyramid approaches have been proposed to speed up the registration process and increase the accuracy of th...

A suite of parallel algorithms for ordering DNA sequences (termed PARODS) is presented. The algorithms in PARODS are based on an earlier serial algorithm, ODS, which is a physical mapping algorithm based on simulated annealing. Parallel algorithms for simulated annealing based on Markov chain decomposition are proposed and applied to the problem of physical mapping. Perturbation methods and pro...

The research presented here is a comparison of the scalability of the simulated annealing algorithm on a vector super computer (CRAY Y-MP) with the scalability of a parallel implementation on a massively parallel transputer surface (Parsytec GCel with 512 nodes of type T805). Some results of the annealing procedure applied to the crystallization of Lennard-Jones particles on a sphere are presen...