A simultaneous cost-risk reduction optimisation in JIT systems using genetic algorithms

This paper presents the implementation of Just-in-Time (JIT) approach in production systems, which plays a significant role in minimising costs and performances of products and services supplied to the global marketplace. However, there are many potential risks that cause significant disruptions to all supply chain members. In this paper, a genetic algorithm model is developed for simultaneously reducing the total cost of a final product and the potential risks associated with these benefits. Specifically, it demonstrates the effectiveness of a genetic algorithm approach for optimising the JIT model developed in [1]. The proposed model is validated with experiments using simple case studies. The findings demonstrate the effectiveness of the developed GA in solving such issue.