Enhancing decision of supplier selection using a genetic algorithm: A case study

This paper takes a practical case study approach to demonstrate the genetic algorithm (GA)'s ability to help purchasing manager in making a better decision on procurement of products or materials. The GA implemented in the supplier selection function aims to allow purchasing managers to get better decisions in choosing the appropriate suppliers by choosing the appropriate products under various contextual situations. By allowing the purchasing managers to set their criteria based on priority helps the company to choose good product with best price and best quality, thus decreases procurement budget while increases company reputation. Information regarding evaluation criteria and data for our experiments are obtained through a local company which provides automobile service and repairs. Results generated from experiments based on various scenarios by prioritizing different evaluation attributes have demonstrated the GA's ability in choosing the “fittest” solution.