Holonic-C2 Organization Structure Generation Method Based on Clustering Optimization Algorithms

Abstract

For Holonic-C2 organization-structure generation, a set of methods based on task-cluster clustering and platform-set optimization are proposed. Initially, the mathematical descriptions of the Holonic-C2 organization components are presented, and the characteristics and advantages of the Holonic-C2 organization are analyzed. To address the critical problems of task cluster and platform-set construction in the organization structure, with the equalization of the task resource requirements and platform resource capabilities, the mathematical models for two-stage clustering optimization are established, respectively. The multi-view clustering optimization and neighborhood search artificial bee colony algorithms are proposed and applied, respectively, for solving these mathematical models. Finally, Monte Carlo simulations are performed, and the obtained results demonstrate the effectiveness of the proposed models and algorithms.