Network revenue management under specic choice models

New challenges in the business environment, such as increased competition andthe inuence of the internet on main distribution channels has led to fundamental changesin traditional revenue management models. under these conditions, modeling individualdecisions more accurately is becoming a key factor. nearly all research studies about choicebasedrevenue management models use the well-known multinomial logit model. thismodel has one important restriction, that is, the independence of irrelevant alternatives; aproperty which states that the ratio of choice probabilities for two distinct alternatives isindependent of the attributes of any other alternatives. in this paper, a nested logit model isproposed for removing this limitation and incorporating a correlation between alternativesin each nest. the new subproblem of column generation is introduced and a combinationof heuristic and metaheuristic algorithms for solving this problem is provided. interestingoutcomes are obtained during analysis of the results of experimental computations, suchas oer sets and iteration trends, with respect to the correlation measure inside eachnest. simulation results show that, although changing the choice model might lead tosignicant improvement in revenue under some conditions, during all scenarios, observingthe correlation should not cause the choice model to change immediately.