The Experts below are selected from a list of 60 Experts worldwide ranked by ideXlab platform

Daniel Diaz - One of the best experts on this subject based on the ideXlab platform.

  • Recommendation Heuristics for Improving Product Line Configuration Processes
    2014
    Co-Authors: Raul Mazo, Camille Salinesi, Cosmin Dumitrescu, Daniel Diaz
    Abstract:

    In mass customization industries, such as car manufacturing, configurators play an important role both to interact with customers and in engineering processes. This is particularly true when engineers rely on reuse of assets and product line engineering techniques. Theoretically, product line Configuration should be guided by the product line model. However, in the industrial context, the Configuration of products from product line models is complex and error prone due to the large number of variables in the models. The Configuration Activity quickly becomes cumbersome due to the number of decisions needed to get a proper Configuration, to the fact that they should be taken in pre-defined order, or the poor response time of configurators when decisions are not appropriate. This chapter presents a collection of recommendation heuristics to improve the interActivity of product line Configuration so as to make it scalable to common engineering situations.We describe the principles, benefits and the implementation of each heuristic using constraint programming. The application and usability of the heuristics is demonstrated using a case study from the car industry.

  • Recommendation Systems in Software Engineering - Recommendation Heuristics for Improving Product Line Configuration Processes
    Recommendation Systems in Software Engineering, 2013
    Co-Authors: Raul Mazo, Camille Salinesi, Cosmin Dumitrescu, Daniel Diaz
    Abstract:

    In mass customization industries, such as car manufacturing, configurators play an important role both to interact with customers and in engineering processes. This is particularly true when engineers rely on reuse of assets and product line engineering techniques. Theoretically, product line Configuration should be guided by the product line model. However, in the industrial context, the Configuration of products from product line models is complex and error-prone due to the large number of variables in the models. The Configuration Activity quickly becomes cumbersome due to the number of decisions needed to get a proper Configuration, to the fact that they should be taken in predefined order, or the poor response time of configurators when decisions are not appropriate. This chapter presents a collection of recommendation heuristics to improve the interActivity of product line Configuration so as to make it scalable to common engineering situations. We describe the principles, benefits, and the implementation of each heuristic using constraint programming. The application and usability of the heuristics is demonstrated using a case study from the car industry.

  • Constraints: the Heart of Domain and Application Engineering in the Product Lines Engineering Strategy
    International Journal of Information System Modeling and Design, 2012
    Co-Authors: Raul Mazo, Camille Salinesi, Daniel Diaz, Olfa Djebbi, Alberto Lora-michiels
    Abstract:

    Drawing from an analogy between features based Product Line (PL) models and Constraint Programming (CP), this paper explores the use of CP in the Domain Engineering and Application Engineering activities that are put in motion in a Product Line Engineering strategy. The start idea is simple: both CP and PL engineering deal with variables, and constraints that these variables must satisfy. Therefore, specifying a PL as a constraint program instead of a feature model, or another kind of PL formalism, carries out two important qualities of CP: expressiveness and direct automation. On the one hand, variables in CP can take values over boolean, integer, real or even complex domains (i.e., lists, arrays and trees) and not only boolean values as in most PL languages such as the Feature-Oriented Domain Analysis (FODA). Specifying boolean, arithmetic, symbolic and reified constraint, provides a power of expression that spans beyond that provided by the boolean dependencies in FODA models. On the other hand, PL models expressed as constraint programs can directly be executed and analyzed by off-the-shelf solvers. Starting with a working example, this paper explores the issues of (a) how to specify a PL model using CP, including in the presence of multi-model representation, (b) how to verify PL specifications, (c) how to specify Configuration requirements and (d) how to support the product Configuration Activity. Tests performed on a benchmark of 50 PL models show that the approach is efficient and scales up easily to very large and complex PL specifications

  • constraints the heart of domain and application engineering in the product lines engineering strategy
    International Journal of Information System Modeling and Design, 2012
    Co-Authors: Raul Mazo, Camille Salinesi, Daniel Diaz, Olfa Djebbi, Alberto Loramichiels
    Abstract:

    Drawing from an analogy between features based Product Line PL models and Constraint Programming CP, this paper explores the use of CP in the Domain Engineering and Application Engineering activities that are put in motion in a Product Line Engineering strategy. Specifying a PL as a constraint program instead of a feature model carries out two important qualities of CP: expressiveness and direct automation. On the one hand, variables in CP can take values over boolean, integer, real or even complex domains and not only boolean values as in most PL languages such as the Feature-Oriented Domain Analysis FODA. Specifying boolean, arithmetic, symbolic and reified constraint, provides a power of expression that spans beyond that provided by the boolean dependencies in FODA models. On the other hand, PL models expressed as constraint programs can directly be executed and analyzed by off-the-shelf solvers. This paper explores the issues of a how to specify a PL model using CP, including in the presence of multi-model representation, b how to verify PL specifications, c how to specify Configuration requirements, and d how to support the product Configuration Activity. Tests performed on a benchmark of 50 PL models show that the approach is efficient and scales up easily to very large and complex PL specifications.

Raul Mazo - One of the best experts on this subject based on the ideXlab platform.

  • Recommendation Heuristics for Improving Product Line Configuration Processes
    2014
    Co-Authors: Raul Mazo, Camille Salinesi, Cosmin Dumitrescu, Daniel Diaz
    Abstract:

    In mass customization industries, such as car manufacturing, configurators play an important role both to interact with customers and in engineering processes. This is particularly true when engineers rely on reuse of assets and product line engineering techniques. Theoretically, product line Configuration should be guided by the product line model. However, in the industrial context, the Configuration of products from product line models is complex and error prone due to the large number of variables in the models. The Configuration Activity quickly becomes cumbersome due to the number of decisions needed to get a proper Configuration, to the fact that they should be taken in pre-defined order, or the poor response time of configurators when decisions are not appropriate. This chapter presents a collection of recommendation heuristics to improve the interActivity of product line Configuration so as to make it scalable to common engineering situations.We describe the principles, benefits and the implementation of each heuristic using constraint programming. The application and usability of the heuristics is demonstrated using a case study from the car industry.

  • Recommendation Systems in Software Engineering - Recommendation Heuristics for Improving Product Line Configuration Processes
    Recommendation Systems in Software Engineering, 2013
    Co-Authors: Raul Mazo, Camille Salinesi, Cosmin Dumitrescu, Daniel Diaz
    Abstract:

    In mass customization industries, such as car manufacturing, configurators play an important role both to interact with customers and in engineering processes. This is particularly true when engineers rely on reuse of assets and product line engineering techniques. Theoretically, product line Configuration should be guided by the product line model. However, in the industrial context, the Configuration of products from product line models is complex and error-prone due to the large number of variables in the models. The Configuration Activity quickly becomes cumbersome due to the number of decisions needed to get a proper Configuration, to the fact that they should be taken in predefined order, or the poor response time of configurators when decisions are not appropriate. This chapter presents a collection of recommendation heuristics to improve the interActivity of product line Configuration so as to make it scalable to common engineering situations. We describe the principles, benefits, and the implementation of each heuristic using constraint programming. The application and usability of the heuristics is demonstrated using a case study from the car industry.

  • Constraints: the Heart of Domain and Application Engineering in the Product Lines Engineering Strategy
    International Journal of Information System Modeling and Design, 2012
    Co-Authors: Raul Mazo, Camille Salinesi, Daniel Diaz, Olfa Djebbi, Alberto Lora-michiels
    Abstract:

    Drawing from an analogy between features based Product Line (PL) models and Constraint Programming (CP), this paper explores the use of CP in the Domain Engineering and Application Engineering activities that are put in motion in a Product Line Engineering strategy. The start idea is simple: both CP and PL engineering deal with variables, and constraints that these variables must satisfy. Therefore, specifying a PL as a constraint program instead of a feature model, or another kind of PL formalism, carries out two important qualities of CP: expressiveness and direct automation. On the one hand, variables in CP can take values over boolean, integer, real or even complex domains (i.e., lists, arrays and trees) and not only boolean values as in most PL languages such as the Feature-Oriented Domain Analysis (FODA). Specifying boolean, arithmetic, symbolic and reified constraint, provides a power of expression that spans beyond that provided by the boolean dependencies in FODA models. On the other hand, PL models expressed as constraint programs can directly be executed and analyzed by off-the-shelf solvers. Starting with a working example, this paper explores the issues of (a) how to specify a PL model using CP, including in the presence of multi-model representation, (b) how to verify PL specifications, (c) how to specify Configuration requirements and (d) how to support the product Configuration Activity. Tests performed on a benchmark of 50 PL models show that the approach is efficient and scales up easily to very large and complex PL specifications

  • constraints the heart of domain and application engineering in the product lines engineering strategy
    International Journal of Information System Modeling and Design, 2012
    Co-Authors: Raul Mazo, Camille Salinesi, Daniel Diaz, Olfa Djebbi, Alberto Loramichiels
    Abstract:

    Drawing from an analogy between features based Product Line PL models and Constraint Programming CP, this paper explores the use of CP in the Domain Engineering and Application Engineering activities that are put in motion in a Product Line Engineering strategy. Specifying a PL as a constraint program instead of a feature model carries out two important qualities of CP: expressiveness and direct automation. On the one hand, variables in CP can take values over boolean, integer, real or even complex domains and not only boolean values as in most PL languages such as the Feature-Oriented Domain Analysis FODA. Specifying boolean, arithmetic, symbolic and reified constraint, provides a power of expression that spans beyond that provided by the boolean dependencies in FODA models. On the other hand, PL models expressed as constraint programs can directly be executed and analyzed by off-the-shelf solvers. This paper explores the issues of a how to specify a PL model using CP, including in the presence of multi-model representation, b how to verify PL specifications, c how to specify Configuration requirements, and d how to support the product Configuration Activity. Tests performed on a benchmark of 50 PL models show that the approach is efficient and scales up easily to very large and complex PL specifications.

Camille Salinesi - One of the best experts on this subject based on the ideXlab platform.

  • Recommendation Heuristics for Improving Product Line Configuration Processes
    2014
    Co-Authors: Raul Mazo, Camille Salinesi, Cosmin Dumitrescu, Daniel Diaz
    Abstract:

    In mass customization industries, such as car manufacturing, configurators play an important role both to interact with customers and in engineering processes. This is particularly true when engineers rely on reuse of assets and product line engineering techniques. Theoretically, product line Configuration should be guided by the product line model. However, in the industrial context, the Configuration of products from product line models is complex and error prone due to the large number of variables in the models. The Configuration Activity quickly becomes cumbersome due to the number of decisions needed to get a proper Configuration, to the fact that they should be taken in pre-defined order, or the poor response time of configurators when decisions are not appropriate. This chapter presents a collection of recommendation heuristics to improve the interActivity of product line Configuration so as to make it scalable to common engineering situations.We describe the principles, benefits and the implementation of each heuristic using constraint programming. The application and usability of the heuristics is demonstrated using a case study from the car industry.

  • Recommendation Systems in Software Engineering - Recommendation Heuristics for Improving Product Line Configuration Processes
    Recommendation Systems in Software Engineering, 2013
    Co-Authors: Raul Mazo, Camille Salinesi, Cosmin Dumitrescu, Daniel Diaz
    Abstract:

    In mass customization industries, such as car manufacturing, configurators play an important role both to interact with customers and in engineering processes. This is particularly true when engineers rely on reuse of assets and product line engineering techniques. Theoretically, product line Configuration should be guided by the product line model. However, in the industrial context, the Configuration of products from product line models is complex and error-prone due to the large number of variables in the models. The Configuration Activity quickly becomes cumbersome due to the number of decisions needed to get a proper Configuration, to the fact that they should be taken in predefined order, or the poor response time of configurators when decisions are not appropriate. This chapter presents a collection of recommendation heuristics to improve the interActivity of product line Configuration so as to make it scalable to common engineering situations. We describe the principles, benefits, and the implementation of each heuristic using constraint programming. The application and usability of the heuristics is demonstrated using a case study from the car industry.

  • Constraints: the Heart of Domain and Application Engineering in the Product Lines Engineering Strategy
    International Journal of Information System Modeling and Design, 2012
    Co-Authors: Raul Mazo, Camille Salinesi, Daniel Diaz, Olfa Djebbi, Alberto Lora-michiels
    Abstract:

    Drawing from an analogy between features based Product Line (PL) models and Constraint Programming (CP), this paper explores the use of CP in the Domain Engineering and Application Engineering activities that are put in motion in a Product Line Engineering strategy. The start idea is simple: both CP and PL engineering deal with variables, and constraints that these variables must satisfy. Therefore, specifying a PL as a constraint program instead of a feature model, or another kind of PL formalism, carries out two important qualities of CP: expressiveness and direct automation. On the one hand, variables in CP can take values over boolean, integer, real or even complex domains (i.e., lists, arrays and trees) and not only boolean values as in most PL languages such as the Feature-Oriented Domain Analysis (FODA). Specifying boolean, arithmetic, symbolic and reified constraint, provides a power of expression that spans beyond that provided by the boolean dependencies in FODA models. On the other hand, PL models expressed as constraint programs can directly be executed and analyzed by off-the-shelf solvers. Starting with a working example, this paper explores the issues of (a) how to specify a PL model using CP, including in the presence of multi-model representation, (b) how to verify PL specifications, (c) how to specify Configuration requirements and (d) how to support the product Configuration Activity. Tests performed on a benchmark of 50 PL models show that the approach is efficient and scales up easily to very large and complex PL specifications

  • constraints the heart of domain and application engineering in the product lines engineering strategy
    International Journal of Information System Modeling and Design, 2012
    Co-Authors: Raul Mazo, Camille Salinesi, Daniel Diaz, Olfa Djebbi, Alberto Loramichiels
    Abstract:

    Drawing from an analogy between features based Product Line PL models and Constraint Programming CP, this paper explores the use of CP in the Domain Engineering and Application Engineering activities that are put in motion in a Product Line Engineering strategy. Specifying a PL as a constraint program instead of a feature model carries out two important qualities of CP: expressiveness and direct automation. On the one hand, variables in CP can take values over boolean, integer, real or even complex domains and not only boolean values as in most PL languages such as the Feature-Oriented Domain Analysis FODA. Specifying boolean, arithmetic, symbolic and reified constraint, provides a power of expression that spans beyond that provided by the boolean dependencies in FODA models. On the other hand, PL models expressed as constraint programs can directly be executed and analyzed by off-the-shelf solvers. This paper explores the issues of a how to specify a PL model using CP, including in the presence of multi-model representation, b how to verify PL specifications, c how to specify Configuration requirements, and d how to support the product Configuration Activity. Tests performed on a benchmark of 50 PL models show that the approach is efficient and scales up easily to very large and complex PL specifications.

Zhili Zhang - One of the best experts on this subject based on the ideXlab platform.

Rajkumar Roy - One of the best experts on this subject based on the ideXlab platform.

  • A framework for cost evaluation in product service system Configuration
    International Journal of Production Research, 2017
    Co-Authors: Jin Shen, John Ahmet Erkoyuncu, Rajkumar Roy
    Abstract:

    Configuration systems are increasingly used as a means for efficient design of customised product service systems (PSS) to satisfy diverse customer needs. Cost evaluation is thereby important to assist the Configuration engineers in making decisions on feasible Configuration solutions. However, little research attention has been received until recently. To fill this gap, this paper contributes in developing a framework for cost evaluation in PSS Configuration. A holistic view of PSS Configuration, the three-dimensional PSS cost element, and a life cycle-oriented cost evaluation approach are successively proposed. The framework is thereby established with a number of parts, including the preparatory stage, the evaluation stage and the Configuration stage. A pump PSS is illustrated to validate the developed framework. Four feasible Configuration solutions in one Configuration Activity are evaluated and compared. The Configuration engineers are thus assisted with the decision on selecting the one with the least cost