Papers by Keyword: Simulated Annealing Algorithm

Abstract: According to the traditional UMDH network modeling with the least square method to recognize parameters ,it's easy to fall into local minimum ,and with the result that the prediction effect is not ideal. This paper puts forward to combine the simulated annealing algorithm and genetic algorithm, and introduces the combined algorithm to the UMDH network which is used to identify some of its description type coefficient. In this paper ,it describes the simulated annealing genetic algorithm ,and constructs the UMDH network model based on this algorithm, and the model is applied to the simulation of debris flow prediction research ,forecast average relative error reached 3. 54%. The results show that the algorithm not only ensuring the global optimization but also preventing premature convergence, improve the UMDH network model of global and local searching optimal ability further.

Abstract: In this paper, according to the characteristics and influence factors of the distribution logistics and distribution center problem, a mathematical model of the distribution center of the LRTWP (Location and Routing with Time Window Problem) was established. An improved simulated annealing algorithm was used to solve the model, the parameter and selection operator in the algorithm is setted reasonably. Simulations and results indicate that the improved simulated annealing algorithm has better feasibility and validity for solving the LRTWP.

Abstract: In this study, the author focus on the exchange rate forecasting. Exchange rates fluctuation is extremely complex, not only contains the linear part but also includes non-linear elements, In this paper, Simulated Annealing Algorithm is introduced to overcome the neural network easy fall into local minimum defects in BP neural network basis, in order to optimize the network weights and thresholds, and thus improve the prediction accuracy. Through several forecast experiments about the major currencies against, the result show that compare to the single use of BP neural network, after introduced Simulated Annealing Algorithm, the prediction accuracy and stability has been further improved, meanwhile time-consuming less than genetic algorithms and other optimization algorithms.

Abstract: This paper studies multi-vehicle and multi-cargo loading problem under the limited mechanical bearing capacity. Tabu search algorithm is an algorithm based on neighborhood search. According to the features of the problem, the essay centered the construct initial solution to construct neighborhood structure. Firstly, for the operation, 1-move and 2-opt were applied. Secondly, through utilizing Boltzmann mechanism of simulated annealing algorithm, it can also fasten the speed of convergence, and boost the search efficiency. Finally, the good performance of this algorithm can be proved by experiment calculation and the mechanical engineering examples.

Abstract: The efficiency E of a punch for making printed wiring boards is decided by its cost and time. The weight of cost and time is different in different companies. In this paper, we establish a bi-object programming model to measure E. We use an algorithm for obtaining an order of tool switching. Considering how to calculate the shortest path for every tool, we compare three modern optimizationalgorithms. We find Ant colony Algorithm is best in computing the shortest path, but it will cost a lot of time in running. Genetic Algorithm is better than Simulated Annealing Algorithm in time and cost. We make some improvements on these algorithms.

Abstract: we have realized network node of WSN localization algorithm through SA algorithm，and this paper puts forward a method.This method calculate network node and other relevant information through SA algorithm first and then use then as parameters to calculate again.The second calculation is Using BP neural network algorithm. The accuracy of the result has been multiplied compared with the method that does not use BP neural network algorithm

Abstract: In order to allow the user to quickly and accurately search the required information, a query optimization method based on a simulated annealing and particle swarm hybrid algorithm is proposed. The basic idea is: the query population into two flat sub populations, a sub population by using simulated annealing algorithm optimization, another sub populations by using particle swarm algorithm optimization, comparison of two adaptive values, to find the global optimal value. The experimental results show that the mixed algorithm, can further improve the precision and recall of query optimization.

Abstract: In the cable-stayed bridge damage identification index based on the dynamic characteristics, it is the key and premises for cable-stayed bridge damage identification using dynamic index, how to extract the modal of structure exactly through optimal placement of sensors. This article uses simulated annealing, In line with the modal assurance criterion, extract mechanical analysis data of Zhangzhen cable-stayed bridge ANSYS finite element model and obtain optimized acceleration sensor layout scheme of main beam. Based on this optimization scheme we carry out a dynamic characteristics test on Zhangzhen cable-stayed bridge. Through the comparison between observation results and calculation results, we find they are very closely. To verify that the simulated annealing algorithm based on modal assurance criterion used in cable-stayed bridge acceleration sensors optimized is effective, viable, and correct.

Abstract: This paper analyzes the PHY layer of IEEE 802.11 standards for a variety of transmission rate, after learned that MAC layer does not provide for its adaptive approach. With the study of various adaptive algorithms, the SAARF protocol based on simulated annealing algorithm is proposed on MAC Layer rate adaptation, which can adaptively adjust transmitting rate. Compared with ARF (Auto Rate Fallback) protocol, SAARF can more effectively improve the throughput from the simulation results.

Abstract: The Sweden method of slices is used as the data model for slope stability analysis and a new searching method for slope stability analysis is presented. This method, named SAA_IAFSA in this paper uses the artificial fish-swarm algorithm based on simulated annealing algorithm to search the critical failure surface and minimum safety factor. This method can overcome the disadvantages of traditional optimization method such as easy to fall into local extreme points with high accuracy, applicability, and can get a more accurate global optimal solution. Finally, the feasibility and effectiveness of the new approach is verified by practical problem. The experimental results show that the proposed algorithm is significantly superior to original AFSA, with wide application.