Reliability-based total cost of ownership approach for supplier selection using cuckoo-inspired hybrid algorithm

Abstract

In today’s highly competitive environment, an effective supplier selection process is very important to the success of any manufacturing organization. A number of models and techniques have been developed to deal with supplier selection and evaluation methods. Traditional supplier selection methods are often based on the quoted initial price, which ignores the significant direct and indirect costs associated with quality, usage, maintenance, and service cost. This paper will look at the reliability-based total cost of ownership (RBTCO) approach which accounts both direct and indirect costs, as applied to the supplier selection process. The mathematical formulation of RBTCO for supplier selection problem fits into the nonlinear integer programming problem, which belongs to the NP-hard category. In this paper, a recently developed meta-heuristic optimization algorithm, cuckoo search (CS) hybridized with well-known genetic algorithm called HCSGA is proposed to solve the supplier selection problem. By embedding the genetic operators in standard CS, the balance between the exploration and exploitation ability further improved and more search space are observed during the algorithms’ performance. The computational test results show that the proposed hybrid algorithm significantly improves the original cuckoo search algorithm for small and larger sized problem instances.