A New High-Efficiency Global Optimization Algorithm for Solving Traveling Salesman Problem

2012 ◽  
pp. 649-656
Author(s):  
Daibo Liu ◽  
Mengshu Hou ◽  
Hong Qu ◽  
Pu Xiong
Keyword(s):  
Global Optimization ◽  
Traveling Salesman Problem ◽  
Optimization Algorithm ◽  
High Efficiency ◽  
Traveling Salesman ◽  
Global Optimization Algorithm

A New Optimization Algorithm for Inverse Analysis to Material Parameters

2008 ◽  
Vol 575-578 ◽  
pp. 1013-1019
Author(s):  
Ying Hui Lu ◽  
Shui Lin Wang ◽  
Hao Jiang
Keyword(s):  
Global Optimization ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Linear Correlation ◽  
Inverse Analysis ◽  
High Efficiency ◽  
Global Optimization Algorithm ◽  
Local Optima ◽  
Material Parameters ◽  
Non Linear

the inverse analysis to material parameters is often translated into an optimization for an objective function, based on the correlation between the material parameters and the foregone information. But mostly because of the non-linear correlation, a good optimization algorithm with the capabilities to avoid being trapped by local optima is required during the process of optimization. So the present paper proposes a new global optimization algorithm, which couples the dynamic canonical descent algorithm and the improved Powell’s algorithm. The high efficiency of the new algorithm is shown on four known problems classically for testing optimization algorithms and finally, in the non-linear inverse analysis, the new algorithm is used for optimizing an objective function to get material parameters rightly.

scholarly journals An Improved Whale Optimization Algorithm for the Traveling Salesman Problem

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 48
Author(s):  
Jin Zhang ◽  
Li Hong ◽  
Qing Liu
Keyword(s):  
Traveling Salesman Problem ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Relevant Literature ◽  
Population Diversity ◽  
Traveling Salesman ◽  
Whale Optimization Algorithm ◽  
Neighborhood Search ◽  
Whale Optimization ◽  
The Traveling Salesman Problem

The whale optimization algorithm is a new type of swarm intelligence bionic optimization algorithm, which has achieved good optimization results in solving continuous optimization problems. However, it has less application in discrete optimization problems. A variable neighborhood discrete whale optimization algorithm for the traveling salesman problem (TSP) is studied in this paper. The discrete code is designed first, and then the adaptive weight, Gaussian disturbance, and variable neighborhood search strategy are introduced, so that the population diversity and the global search ability of the algorithm are improved. The proposed algorithm is tested by 12 classic problems of the Traveling Salesman Problem Library (TSPLIB). Experiment results show that the proposed algorithm has better optimization performance and higher efficiency compared with other popular algorithms and relevant literature.

A global optimization algorithm for solving a four-person game

2017 ◽  
Vol 13 (3) ◽  
pp. 587-596
Author(s):  
S. Batbileg ◽  
N. Tungalag ◽  
A. Anikin ◽  
A. Gornov ◽  
E. Finkelstein
Keyword(s):  
Global Optimization ◽  
Optimization Algorithm ◽  
Global Optimization Algorithm ◽  
Person Game
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