Construct Linear Polynomial Complementary Transformation for NP-Completeness Using Parallel Genetic Algorithm

This paper examines the correlation between numbers of computer cores in parallel genetic algorithms. The objective to determine the linear polynomial complementary equation in order represent the relation between number of parallel processing and optimum solutions. Model this relation as optimization function (f(x)) which able to produce many simulation results. F(x) performance is outperform genetic algorithms. Compression results between genetic algorithm and optimization function is done. Also the optimization function give model to speed up genetic algorithm. Optimization function is a complementary transformation which maps a TSP given to linear without changing the roots of the polynomials.

• Publication year

  2016

• Venue

  Unknown venue

• Publication date

  2016-11-07

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.20944/PREPRINTS201611.0033.V1
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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