The simulated countercurrent moving-bed chromatographic reactor (SCMCR) has been reported to significantly enhance methane conversion and C2 product yield for oxidative coupling of methane (OCM) reaction, which is otherwise a low per pass conversion reaction. A mathematical model of an unconventional three-section SCMCR for OCM was first developed and solved using numerically tuned kinetic and adsorption parameters. The model predictions showed good agreement with available experimental results of SCMCR for OCM. Effects of several process parameters on the performance of SCMCR were investigated. A multi-objective optimisation problem was solved at the operating stage using state-of-the-art AI-based non-dominated sorting genetic algorithm with jumping genes adaptations (NSGA-II-JG), which resulted in Pareto Optimal solutions. It was found that the performance of the SCMCR could be significantly improved under optimal operating conditions. (c) 2011 Canadian Society for Chemical Engineering