Research on an Improved Random Weight GA Based on Heap Sort

Wu Xue Jiang; Min Xia Liu; Ji'an Tan

doi:10.4028/www.scientific.net/AMR.926-930.3183

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 926-930Research on an Improved Random Weight GA Based on...

Research on an Improved Random Weight GA Based on Heap Sort

Abstract:

Multi-objective optimization is a kind of optimization commonly existed in the engineering practice, and the GA is widely applied in the multi-objective optimization issue. In order to improve the GA’s effect on the multi-objective optimization issue, the paper proposes the improved strategy, introduces the heap sort mechanism, improves the scouting speed of GA, reduces the convergence range, reduces the time complexity and spatial complexity. Through the example simulation, the effectiveness and superiority of the improved strategy are proved.

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Periodical:

Advanced Materials Research (Volumes 926-930)

Pages:

3183-3186

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.926-930.3183

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Online since:

May 2014

Authors:

Wu Xue Jiang*, Min Xia Liu, Ji'an Tan

Keywords:

Genetic Algorithm (GA), Heap Sort, Multi-Objective Optimization (MOP), Pareto Optimal Solution

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