An exact method for assortment optimization under the nested logit model
نویسندگان
چکیده
We study the problem of finding an optimal assortment products maximizing expected revenue, in which customer preferences are modeled using a nested logit choice model. This is known to be polynomially solvable specific case and NP-hard otherwise, with only approximation algorithms existing literature. provide exact general method that embeds tailored Branch-and-Bound algorithm into fractional programming framework. In contrast literature, assumptions imposed on either structure nests or combination characteristics products, no input data imposed. Although our approach not polynomial size, it can solve most setting for large-size instances. show scheme’s parameterized subproblem, highly non-linear binary optimization problem, decomposable by nests, primary advantage approach. To subproblem each nest, we propose two-stage first stage, fix large set variables based single-nest subproblem’s newly-derived structural properties. significantly reduce size. second design problem-specific upper bounds. Numerical results able instances five up 5000 per nest. The challenging those mix nests’ dissimilarity parameters, where some them smaller than one others greater one.
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ژورنال
عنوان ژورنال: European Journal of Operational Research
سال: 2021
ISSN: ['1872-6860', '0377-2217']
DOI: https://doi.org/10.1016/j.ejor.2020.12.007