Cryogenic liquids such as liquid oxygen and liquid hydrogen are extensively used in many processes and manufacturing industries. In these industries, transferring cryogens via pipelines is a routine phenomenon. As the boiling points and latent heat of cryogens are low, excessive vaporization of these cryogens is innate. Therefore, ensuring that the cryogen reaches the utility in its liquid form is challenging. In the case of liquid hydrogen and liquid helium, the pipelines are jacketed with a high boiling cryogen like nitrogen. The idea is to dump most of the heat into cheap nitrogen to limit the loss of precious hydrogen or helium. From a heat inleak point, maximizing the amount of nitrogen in the jacket is advantageous by choosing large cross‐sectional areas. Also, larger flow cross sections would lower pressure drops and, therefore, lower pumping costs. However, such a choice would add to the mass of the pipeline. An increase in the mass of the pipeline increases the need for better structural support of the pipeline assembly. Therefore, the design of cryogen jackets for limiting heat inleak is a multi‐objective optimization problem. In this work, we model the heat leak into the hydrogen via the nitrogen jacket and the pressure drop of liquid nitrogen, and we find the mass of the pipeline assembly. Then, we optimize the design of nitrogen jackets fitted over hydrogen pipelines. We employ the evolutionary optimization technique, genetic algorithm (GA), to perform this optimization.cryogen; genetic algorithm; heat inleak; liquid hydrogen; optimization.