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An Extended Artificial Physics Optimization Algorithm for Global Optimization Problems | IEEE Conference Publication | IEEE Xplore

An Extended Artificial Physics Optimization Algorithm for Global Optimization Problems


Abstract:

Artificial Physics Optimization (APO) algorithm inspired by natural physical forces is a population-based stochastic algorithm based on Physicomimetics framework. In this...Show More

Abstract:

Artificial Physics Optimization (APO) algorithm inspired by natural physical forces is a population-based stochastic algorithm based on Physicomimetics framework. In this paper, an extended APO (EAPO) algorithm is presented through considering the personal best positions of all individual, which can provide much useful information for search. In EAPO algorithm, the velocity updated equation is similar to that of PSO algorithm. By comparison and analysis, we can consider that EAPO algorithm is a general form of PSO algorithm and has a better diversity than PSO algorithm. The simulation results confirm that EAPO is an effective stochastic population-based search algorithm. Meanwhile, a comparison with other population-based heuristics shows that EAPO algorithm is competitive.
Date of Conference: 07-09 December 2009
Date Added to IEEE Xplore: 17 February 2010
ISBN Information:
Conference Location: Kaohsiung, Taiwan

References

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