Greedy-Like Algorithms for Dynamic Assortment Planning Under Multinomial Logit Preferences
نویسندگان
چکیده
منابع مشابه
Assortment Optimization under Unknown MultiNomial Logit Choice Models
Motivated by e-commerce, we study the online assortment optimization problem. The seller offers an assortment, i.e. a subset of products, to each arriving customer, who then purchases one or no product from her offered assortment. A customer’s purchase decision is governed by the underlyingMultiNomial Logit (MNL) choice model. The seller aims to maximize the total revenue in a finite sales hori...
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We study the assortment optimization problem under the Sequential Multinomial Logit (SML), a discrete choice model that generalizes the multinomial logit (MNL). Under the SML model, products are partitioned into two levels, to capture differences in attractiveness, brand awareness and, or visibility of the products in the market. When a consumer is presented with an assortment of products, she ...
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We consider constrained assortment problems assuming that customers select according to the multinomial logit model (MNL). The objective is to find an assortment that maximizes the expected revenue per customer and satisfies a set of totally unimodular constraints. We show that this fractional binary problem can be solved as an equivalent linear program. We use this result to solve five classes...
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The assortment optimization problem under the mixture of multinomial logit models is NPcomplete and there are different approximation methods to obtain upper bounds on the optimal expected revenue. In this paper, we analytically compare the upper bounds obtained by the different approximation methods. We propose a new, tractable approach to construct an upper bound on the optimal expected reven...
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We study robust formulations of assortment optimization problems under the multinomial logit choice model. The novel aspect of our formulations is that the true parameters of the logit model are assumed to be unknown, and we represent the set of likely parameter values by a compact uncertainty set. The objective is to find an assortment that maximizes the worst case expected revenue over all pa...
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ژورنال
عنوان ژورنال: Operations Research
سال: 2018
ISSN: 0030-364X,1526-5463
DOI: 10.1287/opre.2018.1734