
On Markovian Aspect of Academic Staff Structure in Private Higher Institutions
Author(s) -
O Joshua Magbagbeola Adekunle
Publication year - 2018
Publication title -
international journal of scientific research and management
Language(s) - English
Resource type - Journals
ISSN - 2321-3418
DOI - 10.18535/ijsrm/v6i5.el04
Subject(s) - accreditation , rank (graph theory) , institution , matrix (chemical analysis) , control (management) , pontryagin's minimum principle , differential (mechanical device) , computer science , mathematics , operations research , mathematical optimization , political science , engineering , optimal control , law , artificial intelligence , materials science , combinatorics , composite material , aerospace engineering
Frustrations, agony and tales of woes that greeted the aftermath of any concluded accreditation exercise informed our interest in addressing this ugly trend that has bedeviled our higher educational system. The dearth or otherwise absence of an appropriate model(s) that will satisfy both the starting matrix and the NUCs staff mix by rank matrix explains this disconnect. A typical challenge here is to reach a desired structure by a certain time in a changing environment or with the smallest possible cost in other to meet up with NUC accreditation minimum bench mark requirement for any higher educational institution. The main objective was to reach a desired structure by a certain time in a changing environment or with the smallest possible cost. Therefore a certain degree of control is sensible at various points in time to the attainment of the desired academic staff structure of any higher institution to monitor the academic staff-mix by rank of Academic staff structure of universities not to fall short of NUC requirements for accreditation. In our work, the concept of time as an optimality performance criterion was used to obtain an optimal recruitment control vector for a manpower system modelled by a stochastic differential equation through the necessary condition of Pontryagin theorem. Desired transition matrix P was obtained that is not stochastic but could be further developed into a stochastic matrix as required.