A Parallel Genetic Algorithm Based on Solution Space Division
FENG Yong
GUO Jun
XU Hongyan
FU Xiaoying
Abstract：Genetic algorithm is a kind of the optimization method which is commonly used in NP problem for approximate optimal solution, and it has been widely used in national defense, scientific research, economic management, engineering construction, and other important fields.But some problems often appear during its solving process, such as premature convergence to local optimal solution and the high computational complexity.To solve these problems, first of all, this paper proposes a parallel processing mechanism based on the solution space division which implement parallel processing to solve the optimization problem by dividing the problem solution space.Then the mechanism is introduced into the genetic algorithm, and this paper proposes a parallel genetic algorithm based on the solution space division.Finally, the experimental comparison indicate that the proposed algorithm in parallel processing has a good linear speedup, at the same time overcoming the premature convergence to local optimal solution is better than the standard genetic algorithm and coarse-grained parallel genetic algorithm.
Keywords：solution space divisionparallelizationgenetic algorithmlinear speedupoptimization
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 226-229,271 )