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Entropy 2014, 16(6), 3329-3356;

Speeding up Derivative Configuration from Product Platforms

ETSI Informatica, Universidad Nacional de Educacion a Distancia, Juan del Rosal 16, 28040 Madrid,Spain
Department of Electrical, Electronic and Control Engineering, Universidad de Castilla La Mancha, Ronda de Calatrava 5, 13071 Ciudad Real, Spain
Author to whom correspondence should be addressed.
Received: 16 January 2014 / Revised: 27 May 2014 / Accepted: 9 June 2014 / Published: 18 June 2014
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To compete in the global marketplace, manufacturers try to differentiate their products by focusing on individual customer needs. Fulfilling this goal requires that companies shift from mass production to mass customization. Under this approach, a generic architecture, named product platform, is designed to support the derivation of customized products through a configuration process that determines which components the product comprises. When a customer configures a derivative, typically not every combination of available components is valid. To guarantee that all dependencies and incompatibilities among the derivative constituent components are satisfied, automated configurators are used. Flexible product platforms provide a big number of interrelated components, and so, the configuration of all, but trivial, derivatives involves considerable effort to select which components the derivative should include. Our approach alleviates that effort by speeding up the derivative configuration using a heuristic based on the information theory concept of entropy. View Full-Text
Keywords: entropy-based heuristic; mass customization; product configuration; software product line; feature model entropy-based heuristic; mass customization; product configuration; software product line; feature model

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Heradio, R.; Fernandez-Amoros, D.; Perez-Morago, H.; Adan, A. Speeding up Derivative Configuration from Product Platforms. Entropy 2014, 16, 3329-3356.

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