Computer Science ›› 2020, Vol. 47 ›› Issue (4): 194-203.doi: 10.11896/jsjkx.190200273

• Artificial Intelligence • Previous Articles     Next Articles

Vertical Structure Community System Optimization Algorithm

HUANG Guang-qiu, LU Qiu-qin   

  1. School of Management,Xi’an University of Architecture and Technology,Xi’an 710055,China
  • Received:2019-02-12 Online:2020-04-15 Published:2020-04-15
  • Contact: HUANG Guang-qiu,born in 1964,Ph.D,professor,Ph.D supervisor.His main research interests include petri-net theo-ry and application,system dynamics,swarm intelligent optimization algorithm and computer simulation
  • Supported by:
    This work was supported by the National Natural Science Foundation of China(71874134),Key Project of Natural Science Basic Research Plan of Shaanxi Province(2019JZ-30) and Project of Social Science Foundation of Shaanxi Province(2018S49,2017S035).

Abstract: To solve global optimal solutions of a class of complex non-linear optimization problems,a new algorithm of vertical structure community system optimization,VS-CSO algorithm,is proposed based on the theory of vertical structure community dynamics.In this algorithm,the search space of an optimization problem is regarded as an ecosystem,which has several vertical structure bifurcated nutrient levels and where lives different kinds of biological populations at different nutrient levels; within each population,there are a number of biological individuals living in it; biological individuals can not migrate across populations,but there are interactions among the same population.Populations are linked by cyclic predation-prey or resource-consumption.Using the vertical structure community dynamics model,the all-eating operator,the food-selecting operator,the interference ope-rator,the infection operator,the newborn operator and the death operator are developed.Among them,the all-eating operator and the food-selecting operator can exchange information among individuals across the population,while the interference operator and the infection operator can exchange information among individuals within the population,thus ensuring the full exchange of information among individuals; the newborn operator can timely supplement new individuals into the population,and the death operator can timely eliminate weak individuals from the population,thus greatly improving the ability of the algorithm to jump out of local traps; in the process of solving,VS-CSO algorithm only deals with very few variables at a time,so it can solve high-dimensional optimization problems.The test results show that VS-CSO algorithm can solve a class of very complex optimization problems of single-peak,multi-peak and compound function,and has excellent exploitation ability,exploration ability and coordination of both,and the characteristics of global convergence.The algorithm provides a solution to find global optimal solutions for some complex function optimization problems.

Key words: Global optimal solution, Population dynamics, Swarm intelligence optimization algorithm, Vertical structure community dynamics

CLC Number: 

  • TP301.6
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