Modelling JIT supply chains by simulation and hybrid genetic variable neighbourhood search algorithm

The objective of this study is investigating multi‐stage supply chain systems which is controlled using a kanban system so as to analyse and optimise it. In this paper, a new optimisation approach based on simulation analysis and metaheuristic methods to optimise a multi‐echelon supply chain in a JIT production context is proposed. A hybrid of simulation modelling, genetic algorithm (GA), and variable neighbourhood search (VNS) to solve the above mentioned problem was proposed. In this research paper, GA‐VNS is used iteratively to optimise the supply chain. Furthermore, the performance of the GA and VNS compared with their GA‐VNS counterpart based on their relative error, and it is illustrated that the GA‐VNS has ability to solve NP‐hard problems in the area of complicated simulation optimisation models, especially where there is no prior knowledge of the behaviour of the system.