A Hybrid Vector Artificial Physics Optimization with One-Dimensional Search Method

The direction of each individual velocity vector is very useful information for search in Artificial Physics Optimization (APO) algorithm. APO's simple way to dealing with the errant individual exceeded the lower or upper bounds constrains changes the direction of its motion vector. A shrinkage...

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Bibliographic Details
Main Authors: Gangjun Yang, Liping Xie, Ying Tan, Jianchao Zeng
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Artificial physics optimization
Electronic mail
Force
Global optimization
Newton's Second law
Optimization
Physicomimetics
Search methods
Upper bound
Virtual force
Online Access:Request full text
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Summary:The direction of each individual velocity vector is very useful information for search in Artificial Physics Optimization (APO) algorithm. APO's simple way to dealing with the errant individual exceeded the lower or upper bounds constrains changes the direction of its motion vector. A shrinkage coefficient is introduced to ensure that each individual is within the decision space without changing its direction. One-dimensional search method is merged into the vector model of APO (VM-APO) to improve its local search capability. The simulation results confirm that the performance of the hybrid vector APO with one-dimensional search method is effective.
DOI:10.1109/CASoN.2010.12