Abstract
Scientific evaluation of the competitiveness of China’s dairy industry is of great significance to the development of regional dairy industry. In view of the fact that the existing evaluation model cannot solve the dynamic nonlinear optimization problem, this paper established a projection pursuit model based on accelerating genetic algorithm and carried on the comprehensive evaluation and dynamic analysis on the competitiveness of dairy industry in China’s 31 provinces and cities (not including Hong Kong, Macao, and Taiwan) from five dimensions, namely, basic factors of production, the industry demand conditions, the enterprise competitiveness and growth force, related and supporting industries, and the natural environmental elements. It was found that firstly, from the perspective of time, the development trend of China’s dairy industry basically shows a positive trend. With the improvement of national living standards, the competitiveness of the dairy industry is also constantly improved. Secondly, from the perspective of space, regional differences in the competitiveness of the dairy industry are significant. Inner Mongolia, Heilongjiang, Shandong, and Hebei are at the forefront of the development of the industry, while the development of the dairy industry in the rest of the region has a big gap with those areas. From the perspective of regional layout, the advantageous region of China’s dairy industry has been preliminarily formed, and the competitive advantage is mainly concentrated in the northern region. Accordingly, the countermeasures and suggestions to enhance the competitiveness of China’s dairy industry were put forward.
Highlights
Milk and dairy products are very important parts of healthy diet in the world, which are closely related to people’s life and health
In view of the fact that analytic hierarchy process (AHP), fuzzy comprehensive evaluation, and other models that are greatly influenced by subjective factors are adopted in most relevant evaluation methods, this paper constructed a projection pursuit model (PP), in order to evaluate the competitiveness of dairy industry in 31 provinces and cities in China in a more objective scientific and reasonable way
With the increase of the number of iterations, the convergence speed of accelerating genetic algorithm (AGA) is significantly faster than that of genetic algorithm (GA) and the AGA algorithm close to the horizontal coordinate does not change with the increase of the number of iterations, reflecting its convergence stability and convergence reliability
Summary
Milk and dairy products are very important parts of healthy diet in the world, which are closely related to people’s life and health. Aiming at the above problems, this paper adopted projection pursuit model (PP for short) to comprehensively evaluate and dynamically analyze the competitiveness of dairy industry of 31 provinces and regions in China from 2007 to 2016 and studied the panel data of 31 provinces in China for 10 years, which is comprehensive and can reflect the development and change process of regional dairy competitiveness. E main objectives of this paper are as follows: (1) to build a scientific and reasonable evaluation index system of China’s dairy industry competitiveness and to improve the nonlinear and discrete defects of the PP model by accelerating genetic algorithms; (2) to construct the projection pursuit model with relatively simple algorithm architecture and parameters, which runs an efficient solution algorithm; (3) to achieve comprehensive evaluation and dynamic analysis of the competitiveness of China’s dairy industry from both horizontal and vertical aspects and to find out the characteristics of regional spatial distribution and the main impact factor As China’s dairy industry plays an important role in the national agricultural development strategy, the research in this paper is based on 31 provinces and cities in China, which can quantify the characteristics of each region and guide the development of China’s dairy industry. e main objectives of this paper are as follows: (1) to build a scientific and reasonable evaluation index system of China’s dairy industry competitiveness and to improve the nonlinear and discrete defects of the PP model by accelerating genetic algorithms; (2) to construct the projection pursuit model with relatively simple algorithm architecture and parameters, which runs an efficient solution algorithm; (3) to achieve comprehensive evaluation and dynamic analysis of the competitiveness of China’s dairy industry from both horizontal and vertical aspects and to find out the characteristics of regional spatial distribution and the main impact factor
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