Optimum distribution of resources based on particle swarm optimization and complex network theory

  • Authors:

  • Li-Lan Liu;Zhi-Song Shu;Xue-Hua Sun;Tao Yu

  • Affiliations:

  • Shanghai Enhanced Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai, China;Shanghai Enhanced Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai, China;Shanghai Enhanced Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai, China;Shanghai Enhanced Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai, China

  • Venue:
  • LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part II
  • Year:
  • 2010

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Abstract

The multi-project allocation with constrained resources problems is quite common in manufacturing industry. While relationship and data in enterprise has become complex and bulky along with the leaping development, this makes it far beyond the human experience to optimize the management. Particle Swarm Optimization (PSO) algorithm is then introduced to optimize resources allocation to products. Due to the deficiency of PSO dealing with large scale network, Complex Network theory, good at statistics but not optimization, is firstly introduced to simulate and help analyze the Collaborative Manufacturing Resource network (CMRN) as a complementation. Finally, an optimization is successfully applied to the network with the results presented. Further, these methods could be used for similar researches which integrate PSO with complex network theory.