In this chapter, we focused on proposing a multi-objective strategy to address the conflicting objectives of enhancing image quality while simultaneously reducing image file size in the context of JPEG image compression, primarily through modifications to the quantisation table (QT). To this end, we employ two well-established methods: the non-dominated sorting genetic algorithm (NSGA-II), as a Pareto dominance-based approach, and the reference-point-based NSGA-II (NSGA-III), as a decomposition-based approach. By integrating our proposed strategy into these algorithms, we introduce two novel multi-objective techniques, namely NSGAII-JPEG and NSGAIII-JPEG. Our approach is designed to generate a diverse set of solutions, allowing users to select the most suitable solution based on their preferences after the optimisation process concludes. Our experimental results on different images show the effectiveness of our proposed algorithm.