Backtracking Search Optimization Algorithm with Low-Discrepancy Sequences for Mechanical Design Optimization Problems

Qiu Yan Xu

doi:10.4028/www.scientific.net/AMM.635-637.270

Paper Titles

Vibration Analysis of Rotating Cylindrical Shells
p.253

Vibration Characteristic Optimization of Overhead Weapon Station Based on Dynamic Stability Concept
p.257

Wear Prediction of Ball Screw Based on Adhesive Wear
p.261

Application of Energy-Saving Principle of Mechanical Design in Hydraulic Excavator
p.266

Backtracking Search Optimization Algorithm with Low-Discrepancy Sequences for Mechanical Design Optimization Problems
p.270

Global Sensitivity of Random Parameters in Vibration Transfer Path Systems
p.274

Study on Parameter Identification of Mistuned Blades Based on Static Frequency Test and Finite Element Method
p.281

A Kind of New Automatic Lift Pump
p.285

Analysis on the Mechanics Model of the Electromagnetic Permanent Magnetic Knitting Needle
p.290

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 635-637Backtracking Search Optimization Algorithm with...

Backtracking Search Optimization Algorithm with Low-Discrepancy Sequences for Mechanical Design Optimization Problems

Abstract:

This paper presents the backtracking search optimization algorithm with low-discrepancy sequences to solve mechanical design optimization problems involving problem-specific constraints and many different variables. Similar to other evolutionary algorithms, backtracking search optimization algorithm is sensitive to the initial population. Generally speaking, since there is no information about the optimization problem, the initial population should be created uniformly. The low-discrepancy sequences are employed to increase the uniformity of the initial population. The benchmark problems widely used in the literature of mechanical design optimization are used to evaluate the performance of the presented algorithm. Results show that the proposed algorithm is effective and efficient for solving the mechanical design optimization problems considered.

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Periodical:

Applied Mechanics and Materials (Volumes 635-637)

Pages:

270-273

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.635-637.270

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Online since:

September 2014

Authors:

Qiu Yan Xu*

Keywords:

Backtracking Search Optimization, Evolutionary Algorithm (EA), Low-Discrepancy Sequences, Mechanical Design Optimization

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