simulated annealing


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simulated annealing

A molecular dynamics simulation of system heating and cooling to describe its most stable state.
References in periodicals archive ?
Both algorithm simulated annealing and particle swarm are very convenient to process optimization problem with continuous variables and discrete variables.
Vazquez.:An efficient implementation of parallel simulated annealing algorithm in GPUs, Journal of Global Optimization, vol.
It is the one having // the minimal score produced by the function // "compute_optimal_clusters_with_sim_ann" that use simulated annealing // produce a configuration with a given number of cluster (i in our case) for(i=1 ;i<max_clusters;i++) { cost = compute_optimal_clusters_with_sim_ann(i); if(cost<min_cost) { min_cost = cost; nb_c = i; } } } // The network is now set up previous_score = min_cost; prev_CL_number = nb_c} 4.
For example, Simulated Annealing allows worst solutions to be accepted as the current solution in an attempt to find the optimum [1, 24].
Torabzadeh and Zandieh [49] proposed a cloud theory-based simulated annealing (CSA) algorithm for the 2-stage m-machine assembly flow shop scheduling problem with a bicriteria objective function.
Tsuzuki, "Image reconstruction using interval simulated annealing in electrical impedance tomography," IEEE Transactions on Biomedical Engineering, vol.
This paper transforms the problem of kernel function parameter assignment in traffic flow forecasting to an optimizing searching problem, combines chaos optimization with a simulated annealing algorithm, and uses the randomness and uniformity characteristics of a chaos sequence.
Augmenting simulated annealing to build interaction test suites, in: Proc.
Hence, in this paper a genetic algorithm and a novel population based simulated annealing algorithm are proposed to solve medium and large instances of the PROP.
By combining gradient descent with the global optimization technique of simulated annealing (SA), SARPROP [19] can not only escape local minima but also maintain and improve the training times of the resilient backpropagation (RPROP) algorithm.