Network revenue management under specific choice models

New challenges in the business environment such as increasing competition and influence of Internet as a main distribution channel lead to fundamental changes in traditional revenue management models. Within these conditions, modeling individual’s decisions more accurately is becoming a key factor. Nearly all research studies about the choice-based revenue management models used the well-known multinomial logit model. This model has one important restriction that is called independence of irrelevant alternatives, a property which states that the ratio of choice probabilities for two distinct alternatives is independent of the attributes of any other alternatives.In this paper a nested logit model is proposed for removing this limitation and incorporating correlation between alternatives in each nest. The new subproblem of column generation is introduced and a combination of heuristic and metaheuristic algorithms for solving this problem is provided. Interesting outcomes obtained during analyzing the results of experimental computations such as offer sets and iterations trend with respect to the correlation measure inside each nest. Simulation results show although changing choice model might lead to significant improvement in revenue in some conditions, during all scenarios, observing correlation should not cause to change choice model immediately.