Regional Science and Technology Resource Allocation Optimization Based on Improved Genetic Algorithm

• Hao Xu,
• Lining Xing,
• Lan Huang,

Vol. 11, No. 4, April 29, 2017
10.3837/tiis.2017.04.008, Download Paper (Free):

• Regional science and technology resource
• allocation optimization
• genetic al-gorithm

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 tech-nology systems. Regional science and technology resource allocation optimization is modeled as a double-layer optimization model: the entire system is characterized by top-layer optimi-zation, whereas the subsystems are characterized by bottom-layer optimization. To effica-ciously 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 simu-lation 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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