Institutional Repository
Technical University of Crete
Technical University of Crete
EN
|
EL
| URI | http://purl.tuc.gr/dl/dias/30EE9663-11DC-4FA1-89E0-087B39CDF0B9 | - |
| Identifier | https://doi.org/10.1007/978-3-642-15606-9_19 | - |
| Language | en | - |
| Title | Designing optimal products: Algorithms and systems | en |
| Creator | Matsatsinis Nikolaos | en |
| Creator | Ματσατσινης Νικολαος | el |
| Creator | Tsafarakis Stelios | en |
| Creator | Τσαφαρακης Στελιος | el |
| Publisher | Springer Verlag | en |
| Content Summary | The high cost of a product failure makes it imperative for a company to assess the market penetration of a new product at its early design. In this context, the Optimal Product Line Design problem was formulated thirty five years ago, and remains a significant research topic in the area of quantitative marketing until today. In this chapter we provide a brief description of the problem, which belongs to the class of NP-hard problems, and review the optimization algorithms that have been applied to it. The performance of the algorithms is evaluated, and the best two approaches are applied to simulated data, as well as a real world scenario. Emphasis is placed on Genetic Algorithms, since the results of the study indicate them as the approach that better fits to the specific marketing problem. Finally, the relevant marketing systems that deal with the problem are presented, and their pros and cons are discussed. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-10-21 | - |
| Date of Publication | 2010 | - |
| Bibliographic Citation | Tsafarakis, S., N. Matsatsinis, "Designing Optimal Products: Algorithms and Systems", Marketing Intelligent Systems using Soft Computing: Managerial and Research Applications, Studies in Fuzziness and Soft Computing, vol. 258, pp. 295-336, 2010. DOI: 10.1007/978-3-642-15606-9_19 | en |
Copyright © DIAS 2013
