An Evaluation Model for a Probability Weighted Ontology of Temporal Complexities

Time scheduling in any organization results in complexities depending on the availability of resources to attain optimality in scheduling for effective utilization. Formalizing time schedules using Allen's interval-based relations aids temporal complexity identification and resolution. This work is aimed at modeling and evaluation of temporal complexities in a given temporal schedule in attempt to resolve any existing complexity, thereby providing an optimal schedule. The identified complexity types in the domain of discourse are weighted using the Probability Weighted Ontology (PWO), which is used to explicate the level of optimality of resolutions in the optimized time scheduling system. The golden standard and the human evaluation approaches were adopted in the evaluation of both systems. The selected criteria from these approaches were ranked using the Analytic Hierarchy Process (AHP) to justify the time scheduling systems and determine the efficiency of both systems. The resulting probability weighted ontology allows for efficient ranking of complexities in time schedules towards the production of time schedules with resolved complexity tending to zero.