Construction of urban standard driving cycle based on simulated annealing algorithm optimization

2020 ◽  
Author(s):  
Hang Zhang ◽  
Siwen Lv ◽  
Yu Zhang ◽  
Sumin Zhang
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Driving Cycle ◽  
Algorithm Optimization ◽  
Annealing Algorithm

Simulated Annealing Algorithm Optimization of the Deterred-Coating Propellant Charge Design

2012 ◽  
Vol 496 ◽  
pp. 99-103
Author(s):  
Zhi Tao Liu ◽  
Dan Dan Ji ◽  
Bin Xu ◽  
Hong Xia Jia ◽  
Xin Liao
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Chamber Pressure ◽  
Mass Ratio ◽  
Algorithm Optimization ◽  
Ballistic Performance ◽  
Muzzle Velocity ◽  
Propellant Charge ◽  
Annealing Algorithm ◽  
Charge Design

In order to get better interior ballistic performance of deterred-coating propellant charge (DCPC), the simulated annealing algorithm optimization of DCPC carries out in this paper. The interior ballistic model of DCPC and its model of simulated annealing algorithm optimization are established based on the characteristics of deterred-coating propellant. Two key parameters of DCPC, the mass ratio of deterred-coating propellants to total propellants and the average perforation pressure of deterred-coating propellant，are optimized for the search of the maximum muzzle velocity under the restricting conditions of maximum chamber pressure and the maximum relative end point of combustion. The optimization results agree well with the standard charge parameters, which justifies the feasibility of the model.

Query Optimization Based on the Simulated Annealing and Particle Swarm Optimization

2012 ◽  
Vol 229-231 ◽  
pp. 1870-1873
Author(s):  
Ren Jie Song ◽  
Yan Wang
Keyword(s):  
Simulated Annealing ◽  
Query Optimization ◽  
Simulated Annealing Algorithm ◽  
Particle Swarm ◽  
Optimization Method ◽  
Particle Swarm Algorithm ◽  
Algorithm Optimization ◽  
Optimal Value ◽  
Global Optimal ◽  
Annealing Algorithm

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.

A New Solution for Maxterm Problem in Trigonometric Functions by Simulated Annealing Algorithm

2013 ◽  
Vol 4 (2) ◽  
pp. 20-28
Author(s):  
Farhad Soleimanian Gharehchopogh ◽  
Hadi Najafi ◽  
Kourosh Farahkhah
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Trigonometric Functions ◽  
Matlab Software ◽  
Annealing Algorithm ◽  
Do So

The present paper is an attempt to get total minimum of trigonometric Functions by Simulated Annealing. To do so the researchers ran Simulated Annealing. Sample trigonometric functions and showed the results through Matlab software. According the Simulated Annealing Solves the problem of getting stuck in a local Maxterm and one can always get the best result through the Algorithm.

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