Integration of Genetic Algorithm and Cultural Particle Swarm Algorithms for Constrained Optimization of Industrial Organization and Diffusion Efficiency Analysis in Equipment Manufacturing Industry

Abstract

Aiming at industrial organization multi-objective optimization problem in Equipment Manufacturing Industry, The paper proposes a new type of double layer evolutionary cultural particle swarm optimization algorithm. The algorithm combines the advantages of the particle swarm optimization algorithm and cultural algorithm. It not only revises the problem that the particles are easy to "premature", but also overcomes the drawback of penalty function method. Firstly, improved topology structure of Particle swarm optimization algorithm. Secondly, using crossover strategy and niche competition mechanism. Verified by the test functions, the proposed algorithm has good performance. Through the analysis of the manufacturing performance based on the algorithm, the paper proposes some optimization strategies such as improving the manufacturing industry market concentration, improving the manufacturing level of industry product differentiation and so on.

Keywords

• Particle swarm optimization algorithm
• Cultural algorithm
• Diffusion efficiency analysis
• Industrial organization optimization
• Crossover strategy
• Niche competition mechanism
• Genetic algorithm.