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Soft Computing
Published in: Soft Computing 5/2016

25-02-2015 | Methodologies and Application

Solving the shopping plan problem through bio-inspired approaches

Authors: Francesco Orciuoli, Mimmo Parente, Autilia Vitiello

Published in: Soft Computing | Issue 5/2016

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Abstract

Blended commerce involves all commerce experiences in which customers make use of different channels (online, offline and mobile) for their purchases to take advantages with respect to their needs and attitudes. This new e-commerce trend is typically characterized by so-called loyalty programmes such as coupons and system points. These mechanisms can be extremely useful for the companies to achieve customer retention and for the customers to obtain discounts. However, loyalty programmes can complicate for customers the evaluation of all offers and the selection of optimal providers (shopping plan) for buying the desired set of products. To face this problem, referred as Shopping Plan Problem, optimization algorithms are emerging as a suitable methodology. This paper is aimed at performing a systematic comparison amongst three bio-inspired optimization approaches, genetic algorithms, memetic ones and ant colony optimization, to detect the best performer for solving the shopping plan problem in a blended shopping scenario.
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Metadata
Title
Solving the shopping plan problem through bio-inspired approaches
Authors
Francesco Orciuoli
Mimmo Parente
Autilia Vitiello
Publication date
25-02-2015
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 5/2016
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-015-1625-5

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