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Convex optimization without convexity of constraints on non-necessarily convex sets and its applications in customer satisfaction in automotive industry

  • * Corresponding author: Kamran Jalilian

    * Corresponding author: Kamran Jalilian 
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  • In the present paper, some necessary and su?cient optimality conditions for a convex optimization problem over inequality constraints are presented which are not necessarily convex and are based on convex intersection of non-necessarily convex sets. The oriented distance function and a characterization of the normal cone of the feasible set are used to obtain the optimality conditions. In the second part of the paper, a non-linear smooth optimization model for customer satisfaction in automotive industry is introduced. The results of the first part are applied to solve this problem theoretically.

    Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

    Citation:

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  • Table 1.  The parameters and variables

    Parameters and description
    $ X_{10} $ customer satisfaction of after-sale services in the current year
    $ X_{20} $ customer satisfaction of sale process in the current year
    $ X_{30} $ customer satisfaction of IQS in the current year
    $ X_{40} $ customer satisfaction of APEAL in the current year
    $ \bar{X}_{1}>0 $ at least customer satisfaction of after-sale services
    $ \bar{X}_{2}>0 $ at least customer satisfaction of sale process
    $ \bar{X}_{3}>0 $ at least customer satisfaction of IQS
    $ \bar{X}_{4}>0 $ at least customer satisfaction of APEAL
    $ \mu, \gamma $ parameters in the cost of increasing satisfaction function $ \mathcal{CO}(S_{0}, S_{1}) $
    Variables and description
    $ X_{11} $ customer satisfaction of after-sale services in the next year
    $ X_{21} $ customer satisfaction of sale process in the next year
    $ X_{31} $ customer satisfaction of IQS in the next year
    $ X_{41} $ customer satisfaction of APEAL in the next year
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