A hybrid service supplier selection approach based on variable precision rough set and VIKOR for developing product service system

Abstract

Product service system (PSS) is an important strategy for manufacturing companies to improve competitiveness. The extension of supply range forces the manufacturing companies to select service suppliers to support PSS development due to the constraint of resources and capability. VIKOR approach is applied to evaluate the service suppliers based on compromise programming. To deal with the uncertain evaluation information, evaluation data are expressed as vague values by means of vague set theory. In the vague VIKOR, the maximised group utility and minimised individual regret are obtained based on similarity measure between two vague values. A set of criteria weights is a critical input of VIKOR. The traditional weights-determining approaches are subjective and have higher uncertainty such as analytic hierarchy process and analytic network process. Rough set mining approach can be used to obtain the criteria weights according to the surveyed performance information on each criterion and on the whole. The traditional rough set has poor noise-tolerance capability, the variable precision rough set approach is used to mine the criteria weights, and a mining algorithm is proposed in this paper. A case study of rescue service supplier evaluation in excavator PSS development is presented to illustrate the effectiveness of the proposed approach.

Keywords:

• supplier selection
• variable precision rough set
• VIKOR approach
• vague set theory
• product service system

Acknowledgements

The authors express sincere appreciation to the anonymous referees for their helpful comments to improve the quality of the paper.

Additional information

Funding

The project was supported by the National Natural Science Foundation of China [grant number 71301104]; the Research Fund for the Doctoral Program of Higher Education of China [grant number 20133120120002], [grant number 20120073110096]; the Innovation Program of Shanghai Municipal Education Commission [grant number 14YZ088]; the Shanghai First-class Academic Discipline Project [grant number S1201YLXK]; the Hujiang Foundation of China [grant number A14006].