We consider the assortment optimization problem under the classical two-level nested logit model. We establish a necessary and sufficient condition for the optimal assortment, and use this optimality condition to develop a simple greedy algorithm that iteratively removes at most one product from each nest, until the optimality condition is satisfied. Our algorithm also exploits the beautiful “l...

We consider assortment optimization problems when customers choose according to the nested logit model and there is a capacity constraint limiting the total capacity consumption of all products offered in all nests. When each product consumes one unit of capacity, our capacity constraint limits the cardinality of the offered assortment. For the cardinality constrained case, we develop an effici...

We consider pricing problems when customers choose among the products according to the nested logit model and there is a quality consistency constraint on the prices charged for the products. We consider two types of quality consistency constraints. In the first type of constraint, there is an inherent ordering between the qualities of the products in a particular nest and the price for the pro...

Discrete choice models have been used for several decades to capture central features of customer preferences. In particular, they provide a compact expression of how product demand changes as the offered assortment changes in composition or price. Some models, such as the basic attraction model, have been justified with axioms; see [14]. Alternatively, models like the multinomial logit (MNL) m...

the expected revenue we obtain given that nest i is selected is Ri(wi) = P j∈N wij (κij−ηij logwij) P j∈N wij , where M = {1, . . . ,m}, N = {1, . . . , n} and γi ∈ [0, 1] measures product dissimilarity within nests. Due to a one-to-one relationship, control of the preference weights equates to control of the prices κij−ηij logwij , where 1/ηij represents product price sensitivity and κij/ηij r...

We propose a route choice model that relaxes the independence from irrelevant alternatives property of the logit model by allowing scale parameters to be link specific. Similar to the the recursive logit (RL) model proposed by Fosgerau et al. (2013), the choice of path is modelled as a sequence of link choices and the model does not require any sampling of choice sets. Furthermore, the model ca...

the aim of present article is determining economic value of air pollution and environmental effects of mashhad city air pollution. data of 286 households of mashhad was gathered through questionnaire in a survey reaserch using stratified random sampling method in year 2006. in order to detemine environmental effects of air pollution choice experiment approach - which gives the most perfect envi...

The allocation of combinations of attribute levels to choice situations in stated choice (SC) experiments can have a significant influence upon the resulting study outputs once data is collected. Recently, a small but growing stream of research has looked at using what have become known as efficient SC experimental designs to allocate the attribute levels to choice situations in a manner design...

Upper bound of efficiency loss is a valuable issue for transport network design and planning. This paper initially explores it in a taxed stochastic traffic network whose equilibrium flow pattern is deduced by a cross-nested Logit (CNL) flow assignment model, and a centrally controlling Stackelberg strategy. With the assumptions of separability, nondecreasingness, and convexity of the link time...

A novel approach is proposed to use the Cross Nested Logit (CNL) model in route choice when sampling of paths is considered. It adopts the Metropolis-Hasting algorithm to sample the choice sets for the model. A new expansion factor and an approximation method are put forward to calculate the sampled probabilities of alternatives. We build on state-of-the-art results for the Multivariate Extreme...