An effective AHP-based metaheuristic approach to solve supplier selection problem
This addresses supplier selection for industries needing to balance qualitative and quantitative criteria, but it is incremental as it hybridizes existing methods.
The paper tackles the supplier selection problem, an NP-Complete multi-criteria decision-making issue, by proposing a metaheuristic approach combining Analytic Hierarchy Process (AHP) and Simulated Annealing (SA) with Taguchi design for parameter tuning, and demonstrates results using industry data.
The supplier selection problem is based on electing the best supplier from a group of pre-specified candidates, is identified as a Multi Criteria Decision Making (MCDM), is proportionately significant in terms of qualitative and quantitative attributes. It is a fundamental issue to achieve a trade-off between such quantifiable and unquantifiable attributes with an aim to accomplish the best solution to the abovementioned problem. This article portrays a metaheuristic based optimization model to solve this NP-Complete problem. Initially the Analytic Hierarchy Process (AHP) is implemented to generate an initial feasible solution of the problem. Thereafter a Simulated Annealing (SA) algorithm is exploited to improve the quality of the obtained solution. The Taguchi robust design method is exploited to solve the critical issues on the subject of the parameter selection of the SA technique. In order to verify the proposed methodology the numerical results are demonstrated based on tangible industry data.