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...

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...

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...

In this communication Simulated Annealing and Genetic Algorithms, are applied to the graph partitioning problem. These techniques mimic processes in statistical mechanics and biology, respectively, and are the most popular meta-heuristics or general-purpose optimization strategies. A hybrid algorithm for circuit partitioning, which uses tabu search to improve the simulated annealing meta-heuris...

abstract the muskingum method is frequently used to route floods in hydrology. however, application of the model is still difficult because of the parameter estimation’s. recently, some of heuristic methods have been used in order to estimate the nonlinear muskingum model. this paper presents a efficient heuristic algorithm, simulated annealing, which has been used to estimate the three paramet...

This paper proposes Parallel Simulated Annealing using Genetic Crossover (PSA/GAc). In this algorithm, there are several processes of Simulated Annealing (SA) working parallel. To exchange information between the solutions, the operation of genetic crossover is performed. Through the continuous test problems, it is found that PSA/GAc can search the solution effectively. The proposed algorithm i...

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...

Optimal expansion of medium-voltage power networks is a common issue in electrical distribution planning. Minimizing total cost of the objective function with technical constraints and reliability limits, make it a combinatorial problem which should be solved by optimization algorithms. This paper presents a new hybrid simulated annealing and tabu search algorithm for distribution network expan...

this research presents a new application of the cloud theory-based simulated annealing algorithm to solve mixed model assembly line sequencing problems where line stoppage cost is expected to be optimized. this objective is highly significant in mixed model assembly line sequencing problems based on just-in-time production system. moreover, this type of problem is np-hard and solving this probl...

In this paper, we propose: (a) a restart schedule for an adaptive simulated annealer, and (b) parallel simulated annealing, with an adaptive and parameter-free annealing schedule. The foundation of our approach is the Modified Lam annealing schedule, which adaptively controls the temperature parameter to track a theoretically ideal rate of acceptance of neighboring states. A sequential implemen...