Employing Simulation To Analyse The Effects Of Model Incongruence - With Examples From Airline Revenue Management

Operations research systems are employed to optimize the performance of logistics, transport and supply chain management through solutions based on mathematical models. The scope of these models is constrained not only by the analysts’ knowledge of the system, but also by the computational efficiency of the solution. This restriction can lead to a gap between mathematical models used for solving from conceptual models derived from empirical situations motivating the solutions. This paper claims that simulation models may be employed to analyze and evaluate the effects of the resulting model incongruence. To this end, two types of model incongruence are differentiated, compositional and structural, and two levels of effect are considered separately, short-term and long-term. The concept is illustrated by examples from airline revenue management: A simulation system based on a discrete-event model with multiple agents is used to analyze the effects of parallel flights, competition, and fluctuating demand.