KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Regional Science and Technology Resource Allocation Optimization Based on Improved Genetic Algorithm

  • Xu, Hao (College of Computer Science and Technology, Jilin University) ;
  • Xing, Lining (School of Mathematics and Big Data, Foshan University) ;
  • Huang, Lan (College of Computer Science and Technology, Jilin University)
  • Received : 2016.03.03
  • Accepted : 2017.02.07
  • Published : 2017.04.30
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Abstract

With the advent of the knowledge economy, science and technology resources have played an important role in economic competition, and their optimal allocation has been regarded as very important across the world. Thus, allocation optimization research for regional science and technology resources is significant for accelerating the reform of regional science and technology systems. Regional science and technology resource allocation optimization is modeled as a double-layer optimization model: the entire system is characterized by top-layer optimization, whereas the subsystems are characterized by bottom-layer optimization. To efficaciously solve this optimization problem, we propose a mixed search method based on the orthogonal genetic algorithm and sensitivity analysis. This novel method adopts the integrated modeling concept with a combination of the knowledge model and heuristic search model, on the basis of the heuristic search model, and simultaneously highlights the effect of the knowledge model. To compare the performance of different methods, five methods and two channels were used to address an application example. Both the optimized results and simulation time of the proposed method outperformed those of the other methods. The application of the proposed method to solve the problem of entire system optimization is feasible, correct, and effective.

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References

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