Abstract
Vendor selection is an established problem in supply chain management. It is regarded as a strategic resource by manufacturers, which must be managed efficiently. Any inappropriate selection of the vendors may lead to severe issues in the supply chain network. Hence, the desire to develop a model that minimizes the combination of transportation, deliveries, and ordering costs under uncertainty situation. In this paper, a multi-objective vendor selection problem under fuzzy environment is solved using a fuzzy goal programming approach. The vendor selection problem was modeled as a multi-objective problem, including three primary objectives of minimizing the transportation cost; the late deliveries; and the net ordering cost subject to constraints related to aggregate demand; vendor capacity; budget allocation; purchasing value; vendors’ quota; and quantity rejected. The proposed model input parameters are considered to be LR fuzzy numbers. The effectiveness of the model is illustrated with simulated data using R statistical package based on a real-life case study which was analyzed using LINGO 16.0 optimization software. The decision on the vendor’s quota allocation and selection under different degree of vagueness in the information was provided. The proposed model can address realistic vendor selection problem in the fuzzy environment and can serve as a useful tool for multi-criteria decision-making in supply chain management.
Highlights
One of the most vexing problems facing purchasing managers in organizational business decision-making is a vendor selection problem (VSP)
Vendor selection plays a vital role in supply chain management; this is because of the pressing need to incorporate alliance strategies with the vendors
Research on supply chain and supplier selection has a long tradition since the 1960s, the criteria for vendor selection and vendor rating is a main central area of research in supply chain management (SCM)
Summary
One of the most vexing problems facing purchasing managers in organizational business decision-making is a vendor selection problem (VSP). In the later, the buyer’s requirement cannot be satisfied by a single supplier due to certain constraints listed above and he must decide Uncertainty is another property of VSP because of the imperfect information inherently in the chain, as such fuzzy set theory has to be incorporated to handle the vagueness and imperfections in the decision parameters. The goal programming developed by Charnes et al [4] emerged as a powerful and strong technique for solving multi-criteria decision-making problems. Imprecise input decision parameters are considered to be LR fuzzy numbers, and multi-objective vendor selection problem (MOVSP) is formulated using the concept of fuzzy goal programming with relative weight.
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