A Robust Optimisation Approach of a Simultaneous Cost-Risk Reduction under a Just-in-Time Environment using a Genetic Algorithm

摘要

This paper addresses the problem of simultaneously minimising the total costs of the final product produced by systems adopting a JIT approach. A cost which incorporates both the cost of production processes and the cost arising from the many potential risks associated with any reduction. A robust genetic approach is proposed in order to optimise the novel mathematical model published in. Genetic operators adopted to improve the genetic search algorithm are introduced and discussed. Experiments are conducted to evaluate the performance of the proposed algorithm and an illustrative example is given. A comparison of the genetic operators used is made by means of evaluating different rates, to define the most suitable rate of crossover and mutation. The findings illustrate the effectiveness of the proposed approach in the JIT system with focus on simultaneous cost-risk reduction.