Combining Biological Computation and Fuzzy-Based Methods for Organisationally Cohesive Subgroups
Ikno Kim and Junzo Watada
Cohesive subgroups in complicated employee relationships are commonly discovered and organised when personnel managers need to efficiently execute a job rotation. This provides employees with a better work life quality and encourages them to work more efficiently. Rearranging a small number of employees using electronic computation can be easily accomplished, but rearranging a larger number of employees is NP-hard. This paper proposes an unconventional approach to determine organisationally cohesive subgroups for better job rotation by combining biological computation and fuzzy-based methods to firstly detect all possible employees in cliques and components, secondly find employees in fuzzy cliques, and finally arrange the employees into similar groups. Moreover, the efficiency of performing a fuzzy analysis with biological computation is measured.
Keywords: Biological computation, cohesive subgroup, fuzzy personnel network, job rotation, similarity group.